Function to score responses with fixed item parameters from a previously calibrated LCDM.
Arguments
- calibration.model
the previously calibrated model; an object of class
gdina.- newdata
a required \(N \times I\) matrix. Binary item responses are in the columns.
- q.matrix
a required \(I \times A\) matrix indicating which items measure which attributes.
- attr.prob.fixed
optional argument for attribute profile proportions. Default is uniform distribution of profiles.
- progress
An optional logical indicating whether the function should print the progress of estimation.
Details
Obtain classifications for new responses to items that were previously calibrated. The calibrate-and-score approach is further detailed in Madison et al. (2023).
References
George, A. C., Robitzsch, A., Kiefer, T., Gross, J., & Ünlü , A. (2016). The R package CDM for cognitive diagnosis models. Journal of Statistical Software, 74(2), 1-24.
Henson, R., Templin, J., & Willse, J. (2009). Defining a family of cognitive diagnosis models using log linear models with latent variables. Psychometrika, 74, 191-21.
Madison, M.J., Chung, S., Kim, J., & Bradshaw, L. (2023). Approaches to estimating longitudinal diagnostic classification models. Behaviormetrika.
Examples
## Example 1: T = 2, A = 4
data(data.tdcm01, package = "TDCM")
dat1 <- data.tdcm01$data
qmat1 <- data.tdcm01$q.matrix
pre <- dat1[, 1:20]
post <- dat1[, 21:40]
# calibrate LCDM with post-test data
m1 <- CDM::gdina(data = post, q.matrix = qmat1, linkfct = "logit", method = "ML")
#> -----------------------------------------------------------------
#> CDM 8.2-6 (2022-08-25 15:43:23)
#> GDINA Model
#> Link function: logit
#> ** 2024-02-05 21:05:58.911726
#> -----------------------------------------------------------------
#> ...........................................................
#> Iteration 1 2024-02-05 21:05:58.936217
#> Deviance = 23644.81
#> Maximum parameter change: 0.140968
#> ...........................................................
#> Iteration 2 2024-02-05 21:05:58.98045
#> Deviance = 22969.9 | Deviance change = 674.9129
#> Maximum parameter change: 0.062143
#> ...........................................................
#> Iteration 3 2024-02-05 21:05:59.008306
#> Deviance = 22884.6 | Deviance change = 85.29917
#> Maximum parameter change: 0.210699
#> ...........................................................
#> Iteration 4 2024-02-05 21:05:59.044456
#> Deviance = 22826.78 | Deviance change = 57.81809
#> Maximum parameter change: 0.066469
#> ...........................................................
#> Iteration 5 2024-02-05 21:05:59.068191
#> Deviance = 22819.87 | Deviance change = 6.913551
#> Maximum parameter change: 0.135432
#> ...........................................................
#> Iteration 6 2024-02-05 21:05:59.100638
#> Deviance = 22814.36 | Deviance change = 5.510097
#> Maximum parameter change: 0.024009
#> ...........................................................
#> Iteration 7 2024-02-05 21:05:59.120695
#> Deviance = 22813.63 | Deviance change = 0.7295209
#> Maximum parameter change: 0.06209
#> ...........................................................
#> Iteration 8 2024-02-05 21:05:59.148318
#> Deviance = 22813.24 | Deviance change = 0.3872104
#> Maximum parameter change: 0.013044
#> ...........................................................
#> Iteration 9 2024-02-05 21:05:59.168035
#> Deviance = 22813.04 | Deviance change = 0.1989579
#> Maximum parameter change: 0.058037
#> ...........................................................
#> Iteration 10 2024-02-05 21:05:59.19716
#> Deviance = 22812.9 | Deviance change = 0.1402681
#> Maximum parameter change: 0.014272
#> ...........................................................
#> Iteration 11 2024-02-05 21:05:59.215968
#> Deviance = 22812.82 | Deviance change = 0.0847859
#> Maximum parameter change: 0.01271
#> ...........................................................
#> Iteration 12 2024-02-05 21:05:59.244149
#> Deviance = 22812.78 | Deviance change = 0.0379766
#> Maximum parameter change: 0.005112
#> ...........................................................
#> Iteration 13 2024-02-05 21:05:59.274908
#> Deviance = 22812.76 | Deviance change = 0.013586
#> Maximum parameter change: 0.014065
#> ...........................................................
#> Iteration 14 2024-02-05 21:05:59.302292
#> Deviance = 22812.74 | Deviance change = 0.0194937
#> Maximum parameter change: 0.002715
#> ...........................................................
#> Iteration 15 2024-02-05 21:05:59.320443
#> Deviance = 22812.74 | Deviance change = 0.0023854
#> Maximum parameter change: 0.002621
#> ...........................................................
#> Iteration 16 2024-02-05 21:05:59.342325
#> Deviance = 22812.74 | Deviance change = 0.0011401
#> Maximum parameter change: 0.00174
#> ...........................................................
#> Iteration 17 2024-02-05 21:05:59.360319
#> Deviance = 22812.74 | Deviance change = 0.0009162
#> Maximum parameter change: 0.003531
#> ...........................................................
#> Iteration 18 2024-02-05 21:05:59.385135
#> Deviance = 22812.74 | Deviance change = 0.0009083
#> Maximum parameter change: 0.00087
#> ...........................................................
#> Iteration 19 2024-02-05 21:05:59.400062
#> Deviance = 22812.74 | Deviance change = 0.0001264
#> Maximum parameter change: 0.000805
#> ...........................................................
#> Iteration 20 2024-02-05 21:05:59.420604
#> Deviance = 22812.74 | Deviance change = 0.0001038
#> Maximum parameter change: 0.000744
#> ...........................................................
#> Iteration 21 2024-02-05 21:05:59.434104
#> Deviance = 22812.74 | Deviance change = 8.88e-05
#> Maximum parameter change: 0.000685
#> ...........................................................
#> Iteration 22 2024-02-05 21:05:59.447936
#> Deviance = 22812.74 | Deviance change = 7.72e-05
#> Maximum parameter change: 0.00063
#> ...........................................................
#> Iteration 23 2024-02-05 21:05:59.461079
#> Deviance = 22812.74 | Deviance change = 6.78e-05
#> Maximum parameter change: 0.000578
#> ...........................................................
#> Iteration 24 2024-02-05 21:05:59.474151
#> Deviance = 22812.74 | Deviance change = 6e-05
#> Maximum parameter change: 0.00053
#> ...........................................................
#> Iteration 25 2024-02-05 21:05:59.48731
#> Deviance = 22812.74 | Deviance change = 5.34e-05
#> Maximum parameter change: 0.000486
#> ...........................................................
#> Iteration 26 2024-02-05 21:05:59.500399
#> Deviance = 22812.74 | Deviance change = 4.78e-05
#> Maximum parameter change: 0.000445
#> ...........................................................
#> Iteration 27 2024-02-05 21:05:59.513188
#> Deviance = 22812.74 | Deviance change = 4.29e-05
#> Maximum parameter change: 0.000407
#> ...........................................................
#> Iteration 28 2024-02-05 21:05:59.526269
#> Deviance = 22812.74 | Deviance change = 3.87e-05
#> Maximum parameter change: 0.000372
#> ...........................................................
#> Iteration 29 2024-02-05 21:05:59.539254
#> Deviance = 22812.74 | Deviance change = 3.5e-05
#> Maximum parameter change: 0.000341
#> ...........................................................
#> Iteration 30 2024-02-05 21:05:59.552266
#> Deviance = 22812.74 | Deviance change = 3.17e-05
#> Maximum parameter change: 0.000311
#> ...........................................................
#> Iteration 31 2024-02-05 21:05:59.565162
#> Deviance = 22812.74 | Deviance change = 2.88e-05
#> Maximum parameter change: 0.000285
#> ...........................................................
#> Iteration 32 2024-02-05 21:05:59.584129
#> Deviance = 22812.74 | Deviance change = 2.63e-05
#> Maximum parameter change: 0.00026
#> ...........................................................
#> Iteration 33 2024-02-05 21:05:59.596697
#> Deviance = 22812.74 | Deviance change = 2.4e-05
#> Maximum parameter change: 0.000237
#> ...........................................................
#> Iteration 34 2024-02-05 21:05:59.609297
#> Deviance = 22812.74 | Deviance change = 2.19e-05
#> Maximum parameter change: 0.000217
#> ...........................................................
#> Iteration 35 2024-02-05 21:05:59.621581
#> Deviance = 22812.74 | Deviance change = 2.01e-05
#> Maximum parameter change: 0.000198
#> ...........................................................
#> Iteration 36 2024-02-05 21:05:59.633761
#> Deviance = 22812.74 | Deviance change = 1.84e-05
#> Maximum parameter change: 0.000181
#> ...........................................................
#> Iteration 37 2024-02-05 21:05:59.646062
#> Deviance = 22812.74 | Deviance change = 1.69e-05
#> Maximum parameter change: 0.000165
#> ...........................................................
#> Iteration 38 2024-02-05 21:05:59.657887
#> Deviance = 22812.74 | Deviance change = 1.55e-05
#> Maximum parameter change: 0.00015
#> ...........................................................
#> Iteration 39 2024-02-05 21:05:59.669753
#> Deviance = 22812.74 | Deviance change = 1.43e-05
#> Maximum parameter change: 0.000137
#> ...........................................................
#> Iteration 40 2024-02-05 21:05:59.681852
#> Deviance = 22812.74 | Deviance change = 1.32e-05
#> Maximum parameter change: 0.000125
#> ...........................................................
#> Iteration 41 2024-02-05 21:05:59.693898
#> Deviance = 22812.74 | Deviance change = 1.21e-05
#> Maximum parameter change: 0.000114
#> ...........................................................
#> Iteration 42 2024-02-05 21:05:59.705935
#> Deviance = 22812.74 | Deviance change = 1.12e-05
#> Maximum parameter change: 0.000104
#> ...........................................................
#> Iteration 43 2024-02-05 21:05:59.717869
#> Deviance = 22812.74 | Deviance change = 1.03e-05
#> Maximum parameter change: 9.4e-05
#> -----------------------------------------------------------------
#> Time difference of 0.8782153 secs
# score pre-test responses
m2 <- TDCM::tdcm.score(m1, newdata = pre, q.matrix = qmat1)
#> [1] Scoring responses with item parameters from previously calibrated model.
#> [1] Scoring complete. Check results with the CDM summary function.
summary(m2)
#> -----------------------------------------------------------------
#> CDM 8.2-6 (2022-08-25 15:43:23)
#>
#> Call:
#> CDM::gdina(data = newdata, q.matrix = q.matrix, linkfct = "logit",
#> delta.fixed = calibration.model$delta, attr.prob.fixed = dist,
#> progress = FALSE)
#>
#> Date of Analysis: 2024-02-05 21:05:59.974302
#> Time difference of 0.1258209 secs
#> Computation Time: 0.1258209
#>
#> Generalized DINA Model
#>
#> Number of iterations = 7
#> Iteration with minimal deviance = 7
#>
#> Estimation method: WLS
#> Optimizer: CDM
#> Monotonicity constraints: FALSE
#> Number of items at boundary monotonicity constraint: NA
#>
#> Parameter regularization: FALSE
#>
#> Deviance = 20323.52 | Log likelihood = -10161.76
#>
#> Number of persons = 1000
#> Number of groups = 1
#> Number of items = 20
#> Number of estimated parameters = 0
#> Number of estimated item parameters = 0
#> Number of estimated skill class parameters = 0 ( 16 latent skill classes)
#>
#> AIC = 20324 | penalty = 0 | AIC = -2*LL + 2*p
#> BIC = 20324 | penalty = 0 | BIC = -2*LL + log(n)*p
#> CAIC = 20324 | penalty = 0 | CAIC = -2*LL + [log(n)+1]*p (consistent AIC)
#>
#> -----------------------------------------------------------------
#> Used Q-matrix
#>
#> Att1 Att2 Att3 Att4
#> t1tem1 1 0 0 0
#> t1tem2 1 0 0 0
#> t1tem3 1 0 0 0
#> t1tem4 1 1 0 0
#> t1tem5 1 0 1 0
#> t1tem6 0 1 0 0
#> t1tem7 0 1 0 0
#> t1tem8 0 1 0 0
#> t1tem9 0 1 1 0
#> t1tem10 0 1 0 1
#> t1tem11 0 0 1 0
#> t1tem12 0 0 1 0
#> t1tem13 0 0 1 0
#> t1tem14 0 0 1 1
#> t1tem15 1 0 1 0
#> t1tem16 0 0 0 1
#> t1tem17 0 0 0 1
#> t1tem18 0 0 0 1
#> t1tem19 1 0 0 1
#> t1tem20 0 1 0 1
#>
#> -----------------------------------------------------------------
#>
#> Item Parameter Estimates
#>
#> link item itemno partype rule est se partype.attr
#> 1 logit t1tem1 1 0 GDINA -1.8500 0
#> 2 logit t1tem1 1 1 GDINA 2.5268 0 Att1
#> 3 logit t1tem2 2 0 GDINA -2.0396 0
#> 4 logit t1tem2 2 1 GDINA 2.4801 0 Att1
#> 5 logit t1tem3 3 0 GDINA -1.8284 0
#> 6 logit t1tem3 3 1 GDINA 2.4484 0 Att1
#> 7 logit t1tem4 4 0 GDINA -1.6953 0
#> 8 logit t1tem4 4 1 GDINA 0.3820 0 Att1
#> 9 logit t1tem4 4 2 GDINA 1.2483 0 Att2
#> 10 logit t1tem4 4 1-2 GDINA 1.9649 0 Att1-Att2
#> 11 logit t1tem5 5 0 GDINA -2.1359 0
#> 12 logit t1tem5 5 1 GDINA 1.1610 0 Att1
#> 13 logit t1tem5 5 2 GDINA 1.7450 0 Att3
#> 14 logit t1tem5 5 1-2 GDINA 1.2464 0 Att1-Att3
#> 15 logit t1tem6 6 0 GDINA -1.8011 0
#> 16 logit t1tem6 6 1 GDINA 2.0532 0 Att2
#> 17 logit t1tem7 7 0 GDINA -1.8086 0
#> 18 logit t1tem7 7 1 GDINA 2.1732 0 Att2
#> 19 logit t1tem8 8 0 GDINA -1.9797 0
#> 20 logit t1tem8 8 1 GDINA 2.4459 0 Att2
#> 21 logit t1tem9 9 0 GDINA -1.7141 0
#> 22 logit t1tem9 9 1 GDINA 0.4422 0 Att2
#> 23 logit t1tem9 9 2 GDINA 1.0810 0 Att3
#> 24 logit t1tem9 9 1-2 GDINA 2.5658 0 Att2-Att3
#> 25 logit t1tem10 10 0 GDINA -1.9624 0
#> 26 logit t1tem10 10 1 GDINA 2.2848 0 Att2
#> 27 logit t1tem10 10 2 GDINA 1.2193 0 Att4
#> 28 logit t1tem10 10 1-2 GDINA 0.6186 0 Att2-Att4
#> 29 logit t1tem11 11 0 GDINA -1.7213 0
#> 30 logit t1tem11 11 1 GDINA 2.1766 0 Att3
#> 31 logit t1tem12 12 0 GDINA -1.9910 0
#> 32 logit t1tem12 12 1 GDINA 2.4624 0 Att3
#> 33 logit t1tem13 13 0 GDINA -2.3122 0
#> 34 logit t1tem13 13 1 GDINA 2.7951 0 Att3
#> 35 logit t1tem14 14 0 GDINA -2.2933 0
#> 36 logit t1tem14 14 1 GDINA 1.6906 0 Att3
#> 37 logit t1tem14 14 2 GDINA 2.2520 0 Att4
#> 38 logit t1tem14 14 1-2 GDINA 0.3171 0 Att3-Att4
#> 39 logit t1tem15 15 0 GDINA -1.6254 0
#> 40 logit t1tem15 15 1 GDINA 0.3066 0 Att1
#> 41 logit t1tem15 15 2 GDINA 1.1053 0 Att3
#> 42 logit t1tem15 15 1-2 GDINA 2.4272 0 Att1-Att3
#> 43 logit t1tem16 16 0 GDINA -2.3967 0
#> 44 logit t1tem16 16 1 GDINA 2.9574 0 Att4
#> 45 logit t1tem17 17 0 GDINA -2.1822 0
#> 46 logit t1tem17 17 1 GDINA 2.8343 0 Att4
#> 47 logit t1tem18 18 0 GDINA -2.1807 0
#> 48 logit t1tem18 18 1 GDINA 2.5299 0 Att4
#> 49 logit t1tem19 19 0 GDINA -2.0672 0
#> 50 logit t1tem19 19 1 GDINA 1.9131 0 Att1
#> 51 logit t1tem19 19 2 GDINA 1.4612 0 Att4
#> 52 logit t1tem19 19 1-2 GDINA 0.6771 0 Att1-Att4
#> 53 logit t1tem20 20 0 GDINA -1.8524 0
#> 54 logit t1tem20 20 1 GDINA 3.5267 0 Att2
#> 55 logit t1tem20 20 2 GDINA 1.1167 0 Att4
#> 56 logit t1tem20 20 1-2 GDINA -0.8459 0 Att2-Att4
#>
#> RMSD (RMSEA) Item Fit Statistics
#> t1tem1 t1tem2 t1tem3 t1tem4 t1tem5 t1tem6 t1tem7 t1tem8 t1tem9
#> 0.036 0.055 0.041 0.054 0.037 0.063 0.050 0.055 0.061
#> t1tem10 t1tem11 t1tem12 t1tem13 t1tem14 t1tem15 t1tem16 t1tem17 t1tem18
#> 0.063 0.067 0.043 0.057 0.056 0.045 0.035 0.048 0.053
#> t1tem19 t1tem20
#> 0.044 0.128
#>
#> Mean of RMSEA item fit: 0.055
#> -----------------------------------------------------------------
#> Model Implied Conditional Item Probabilities
#>
#> item rule nessskill itemno skillcomb prob
#> 1 t1tem1 GDINA Att1 1 A0 0.1359
#> 2 t1tem1 GDINA Att1 1 A1 0.6630
#> 3 t1tem2 GDINA Att1 2 A0 0.1151
#> 4 t1tem2 GDINA Att1 2 A1 0.6084
#> 5 t1tem3 GDINA Att1 3 A0 0.1384
#> 6 t1tem3 GDINA Att1 3 A1 0.6502
#> 7 t1tem4 GDINA Att1-Att2 4 A00 0.1551
#> 8 t1tem4 GDINA Att1-Att2 4 A10 0.2119
#> 9 t1tem4 GDINA Att1-Att2 4 A01 0.3901
#> 10 t1tem4 GDINA Att1-Att2 4 A11 0.8699
#> 11 t1tem5 GDINA Att1-Att3 5 A00 0.1057
#> 12 t1tem5 GDINA Att1-Att3 5 A10 0.2739
#> 13 t1tem5 GDINA Att1-Att3 5 A01 0.4035
#> 14 t1tem5 GDINA Att1-Att3 5 A11 0.8825
#> 15 t1tem6 GDINA Att2 6 A0 0.1417
#> 16 t1tem6 GDINA Att2 6 A1 0.5627
#> 17 t1tem7 GDINA Att2 7 A0 0.1408
#> 18 t1tem7 GDINA Att2 7 A1 0.5902
#> 19 t1tem8 GDINA Att2 8 A0 0.1214
#> 20 t1tem8 GDINA Att2 8 A1 0.6145
#> 21 t1tem9 GDINA Att2-Att3 9 A00 0.1526
#> 22 t1tem9 GDINA Att2-Att3 9 A10 0.2189
#> 23 t1tem9 GDINA Att2-Att3 9 A01 0.3468
#> 24 t1tem9 GDINA Att2-Att3 9 A11 0.9149
#> 25 t1tem10 GDINA Att2-Att4 10 A00 0.1232
#> 26 t1tem10 GDINA Att2-Att4 10 A10 0.5799
#> 27 t1tem10 GDINA Att2-Att4 10 A01 0.3223
#> 28 t1tem10 GDINA Att2-Att4 10 A11 0.8966
#> 29 t1tem11 GDINA Att3 11 A0 0.1517
#> 30 t1tem11 GDINA Att3 11 A1 0.6119
#> 31 t1tem12 GDINA Att3 12 A0 0.1202
#> 32 t1tem12 GDINA Att3 12 A1 0.6157
#> 33 t1tem13 GDINA Att3 13 A0 0.0901
#> 34 t1tem13 GDINA Att3 13 A1 0.6185
#> 35 t1tem14 GDINA Att3-Att4 14 A00 0.0917
#> 36 t1tem14 GDINA Att3-Att4 14 A10 0.3537
#> 37 t1tem14 GDINA Att3-Att4 14 A01 0.4897
#> 38 t1tem14 GDINA Att3-Att4 14 A11 0.8772
#> 39 t1tem15 GDINA Att1-Att3 15 A00 0.1645
#> 40 t1tem15 GDINA Att1-Att3 15 A10 0.2110
#> 41 t1tem15 GDINA Att1-Att3 15 A01 0.3728
#> 42 t1tem15 GDINA Att1-Att3 15 A11 0.9015
#> 43 t1tem16 GDINA Att4 16 A0 0.0834
#> 44 t1tem16 GDINA Att4 16 A1 0.6366
#> 45 t1tem17 GDINA Att4 17 A0 0.1014
#> 46 t1tem17 GDINA Att4 17 A1 0.6575
#> 47 t1tem18 GDINA Att4 18 A0 0.1015
#> 48 t1tem18 GDINA Att4 18 A1 0.5864
#> 49 t1tem19 GDINA Att1-Att4 19 A00 0.1123
#> 50 t1tem19 GDINA Att1-Att4 19 A10 0.4616
#> 51 t1tem19 GDINA Att1-Att4 19 A01 0.3530
#> 52 t1tem19 GDINA Att1-Att4 19 A11 0.8791
#> 53 t1tem20 GDINA Att2-Att4 20 A00 0.1356
#> 54 t1tem20 GDINA Att2-Att4 20 A10 0.8421
#> 55 t1tem20 GDINA Att2-Att4 20 A01 0.3240
#> 56 t1tem20 GDINA Att2-Att4 20 A11 0.8749
#> -----------------------------------------------------------------
#>
#> Skill Probabilities
#>
#> skill.prob0 skill.prob1
#> Att1 0.8120 0.1880
#> Att2 0.7066 0.2934
#> Att3 0.5968 0.4032
#> Att4 0.7418 0.2582
#> -----------------------------------------------------------------
#>
#> Polychoric Correlations
#>
#> Group 1
#> Att1 Att2 Att3 Att4
#> Att1 1.000 0.790 0.805 0.758
#> Att2 0.790 1.000 0.771 0.789
#> Att3 0.805 0.771 1.000 0.721
#> Att4 0.758 0.789 0.721 1.000
#>
#> -----------------------------------------------------------------
#>
#> Skill Pattern Probabilities
#>
#> 0000 1000 0100 1100 0010 1010 0110 1110 0001 1001
#> 0.4982 0.0087 0.0356 0.0027 0.1131 0.0156 0.0422 0.0257 0.0324 0.0021
#> 0101 1101 0011 1011 0111 1111
#> 0.0134 0.0038 0.0243 0.0122 0.0527 0.1173
m2$pattern
#> pattern mle.est mle.post map.est map.post post.attr1
#> 1 P1000001 0101 0.7732531 0101 0.6104801 0.0071967608
#> 2 P1000002 1011 0.8558210 1011 0.7576715 0.8167576712
#> 3 P1000003 0101 0.6510035 0111 0.5904542 0.0211450661
#> 4 P1000004 0000 0.6993881 0000 0.9863499 0.0070291677
#> 5 P1000005 0001 0.5333399 0001 0.4864266 0.0060133546
#> 6 P1000006 0110 0.4067857 0000 0.6211876 0.0004680533
#> 7 P1000007 0110 0.9054671 0110 0.8947340 0.0282740130
#> 8 P1000008 0010 0.7399214 0010 0.7014972 0.0002670151
#> 9 P1000009 1001 0.5864788 0001 0.7395102 0.0879363063
#> 10 P1000010 0000 0.7403778 0000 0.9758418 0.0005663039
#> 11 P1000011 0011 0.8692736 0011 0.8401266 0.0291971023
#> 12 P1000012 1101 0.5734254 1111 0.9289315 0.9768768571
#> 13 P1000013 0001 0.6029390 0000 0.4747336 0.0097737400
#> 14 P1000014 0111 0.9913832 0111 0.9928569 0.0025453071
#> 15 P1000015 0000 0.8800457 0000 0.9823247 0.0007988135
#> 16 P1000016 0100 0.4666722 0100 0.4350244 0.0005838629
#> 17 P1000017 0000 0.5886043 0000 0.9700354 0.0065131105
#> 18 P1000018 0001 0.8121305 0000 0.7278233 0.0005848300
#> 19 P1000019 0010 0.5697808 0010 0.8037094 0.0163362005
#> 20 P1000020 0000 0.6248140 0000 0.9483963 0.0018153609
#> 21 P1000021 0011 0.9352733 0011 0.7850855 0.0028506757
#> 22 P1000022 0101 0.4982022 0111 0.7677061 0.0325301578
#> 23 P1000023 1110 0.6297541 1111 0.6875192 0.9702553670
#> 24 P1000024 0000 0.7293857 0000 0.9758475 0.0038118734
#> 25 P1000025 0100 0.8830164 0100 0.5197908 0.0005685068
#> 26 P1000026 1110 0.6352891 1111 0.6915339 0.9757032749
#> 27 P1000027 0100 0.4769848 0000 0.4668873 0.0018364782
#> 28 P1000028 0000 0.8927890 0000 0.9898609 0.0005653722
#> 29 P1000029 0000 0.8321481 0000 0.9775210 0.0005611642
#> 30 P1000030 0000 0.7945936 0000 0.9543939 0.0005500125
#> 31 P1000031 0110 0.9410119 0110 0.9534871 0.0265704455
#> 32 P1000032 0110 0.9423740 0110 0.9530811 0.0193057530
#> 33 P1000033 0000 0.7889528 0000 0.9813444 0.0008876094
#> 34 P1000034 0010 0.4575519 0000 0.6580946 0.0214033744
#> 35 P1000035 0111 0.9821800 0111 0.9679669 0.0310038370
#> 36 P1000036 0110 0.4397752 0000 0.4598777 0.0018410926
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#> 627 P1000627 0010 0.4506039 0000 0.6574211 0.0224048032
#> 628 P1000628 0000 0.4454466 0000 0.8754380 0.0005369583
#> 629 P1000629 0000 0.6837336 0000 0.9630126 0.0008009501
#> 630 P1000630 0000 0.7799658 0000 0.9532099 0.0008513357
#> 631 P1000631 0000 0.5302356 0000 0.9455020 0.0005686134
#> 632 P1000632 0000 0.7565539 0000 0.9766102 0.0005655825
#> 633 P1000633 0100 0.5745958 0000 0.6423557 0.0005722043
#> 634 P1000634 1111 0.9777140 1111 0.9963280 0.9985260821
#> 635 P1000635 1111 0.6620215 1111 0.8257997 0.8283478359
#> 636 P1000636 0011 0.8719551 0011 0.7452931 0.0304495209
#> 637 P1000637 0000 0.8872653 0000 0.9825946 0.0005613861
#> 638 P1000638 1111 0.9959830 1111 0.9983714 0.9984885086
#> 639 P1000639 0110 0.5537806 0110 0.5225916 0.1641882662
#> 640 P1000640 0110 0.8478481 0110 0.6835634 0.0025063751
#> 641 P1000641 0000 0.7481017 0000 0.9615633 0.0005571424
#> 642 P1000642 1111 0.2942821 1111 0.6035305 0.7500301569
#> 643 P1000643 0000 0.9282932 0000 0.9927706 0.0005653600
#> 644 P1000644 0000 0.5465660 0000 0.9342318 0.0005587884
#> 645 P1000645 0000 0.6659797 0000 0.9818709 0.0070294020
#> 646 P1000646 0000 0.5537933 0000 0.8711270 0.0009910953
#> 647 P1000647 1010 0.5008513 0010 0.7187189 0.2257207749
#> 648 P1000648 0111 0.8084284 0111 0.7054375 0.2798862084
#> 649 P1000649 0111 0.7693200 0111 0.8087073 0.0020768466
#> 650 P1000650 0000 0.5191252 0000 0.9203535 0.0062678827
#> 651 P1000651 1101 0.7698671 1111 0.6553109 0.8067405790
#> 652 P1000652 0000 0.7028819 0000 0.9653303 0.0008006936
#> 653 P1000653 0000 0.9282932 0000 0.9927706 0.0005653600
#> 654 P1000654 0000 0.4704682 0000 0.8316430 0.0005034014
#> 655 P1000655 0000 0.5527617 0000 0.8706543 0.0005182244
#> 656 P1000656 0110 0.9066613 0110 0.8366968 0.0015850764
#> 657 P1000657 0000 0.6787328 0000 0.9423833 0.0005508845
#> 658 P1000658 1000 0.3251259 0000 0.8983898 0.0206139013
#> 659 P1000659 0001 0.2914234 0000 0.8551139 0.0110271184
#> 660 P1000660 0001 0.3961301 0000 0.4598741 0.0004457440
#> 661 P1000661 0000 0.6803959 0000 0.9558307 0.0018141874
#> 662 P1000662 0000 0.9282932 0000 0.9927706 0.0005653600
#> 663 P1000663 0000 0.9282932 0000 0.9927706 0.0005653600
#> 664 P1000664 0110 0.6086993 0010 0.6081924 0.0001787328
#> 665 P1000665 0000 0.8878243 0000 0.9894369 0.0005653740
#> 666 P1000666 0100 0.5941708 0100 0.8077193 0.0072398691
#> 667 P1000667 0110 0.5678676 0110 0.3911292 0.0046671213
#> 668 P1000668 0010 0.7544499 0000 0.5715157 0.0003968932
#> 669 P1000669 0010 0.8066376 0010 0.9160029 0.0266028625
#> 670 P1000670 0000 0.9282932 0000 0.9927706 0.0005653600
#> 671 P1000671 0000 0.8800457 0000 0.9823247 0.0007988135
#> 672 P1000672 0011 0.7845487 0011 0.6909931 0.0002734852
#> 673 P1000673 1110 0.8593579 1110 0.7803706 0.9708802140
#> 674 P1000674 0000 0.6045954 0000 0.9739919 0.0070405441
#> 675 P1000675 0000 0.6993881 0000 0.9863499 0.0070291677
#> 676 P1000676 0001 0.4352282 0000 0.9205970 0.0005697921
#> 677 P1000677 1111 0.6633538 1111 0.8257889 0.8289087483
#> 678 P1000678 0100 0.5902861 0000 0.8308240 0.0015301906
#> 679 P1000679 0000 0.4047307 0000 0.9456276 0.0147970630
#> 680 P1000680 0000 0.6133821 0000 0.9244534 0.0005457648
#> 681 P1000681 0110 0.5506304 0110 0.5224430 0.0028524873
#> 682 P1000682 1111 0.9399615 1111 0.9785749 0.9817914494
#> 683 P1000683 0001 0.3473169 0000 0.8862949 0.0132395250
#> 684 P1000684 1111 0.7314775 1111 0.9667063 0.9793115223
#> 685 P1000685 0000 0.6279213 0000 0.9262412 0.0005454679
#> 686 P1000686 0100 0.7771710 0100 0.5499266 0.0037738156
#> 687 P1000687 0110 0.6007382 0110 0.3750470 0.0124251379
#> 688 P1000688 0000 0.3218732 0000 0.8540525 0.0062113934
#> 689 P1000689 0100 0.8435643 0100 0.4914399 0.0038909753
#> 690 P1000690 0000 0.8800457 0000 0.9823247 0.0007988135
#> 691 P1000691 0010 0.8634421 0010 0.8279455 0.0028821687
#> 692 P1000692 0001 0.6687797 0000 0.7762431 0.0068923590
#> 693 P1000693 0101 0.6746320 0111 0.4930822 0.0054664576
#> 694 P1000694 0001 0.6053504 0000 0.6934373 0.0067317613
#> 695 P1000695 0101 0.9644368 0101 0.9475309 0.0064825470
#> 696 P1000696 0000 0.4848045 0000 0.9164606 0.0067890487
#> 697 P1000697 1000 0.8289361 0000 0.8850660 0.1080350368
#> 698 P1000698 0010 0.5999068 0010 0.4912137 0.0157465666
#> 699 P1000699 0100 0.5566640 0100 0.5240657 0.0018514859
#> 700 P1000700 0100 0.4874547 0100 0.7365190 0.0587432667
#> 701 P1000701 1011 0.9352637 1011 0.8216680 0.9798966031
#> 702 P1000702 0000 0.7812679 0000 0.9803424 0.0005662810
#> 703 P1000703 0101 0.6149068 0111 0.5276475 0.0513686908
#> 704 P1000704 0000 0.6989474 0000 0.9347917 0.0005447987
#> 705 P1000705 1110 0.4937392 1111 0.6614127 0.9981609369
#> 706 P1000706 0010 0.7514150 0010 0.8470149 0.0024183191
#> 707 P1000707 0000 0.8927890 0000 0.9898609 0.0005653722
#> 708 P1000708 0001 0.7850017 0000 0.7853981 0.0005807271
#> 709 P1000709 1111 0.8942349 1111 0.9747246 0.9986389269
#> 710 P1000710 0000 0.5309588 0000 0.9519824 0.0094485994
#> 711 P1000711 0111 0.8843963 0111 0.9150738 0.0316259028
#> 712 P1000712 0010 0.7531333 0000 0.4977257 0.0025056268
#> 713 P1000713 1110 0.5239280 1111 0.5903972 0.9963131361
#> 714 P1000714 0000 0.7812679 0000 0.9803424 0.0005662810
#> 715 P1000715 1111 0.9798888 1111 0.9960851 0.9984034372
#> 716 P1000716 1010 0.9330035 1010 0.7820879 0.8065444221
#> 717 P1000717 0111 0.7079287 0111 0.7487440 0.0208364013
#> 718 P1000718 0010 0.3611856 0000 0.7568027 0.0082121513
#> 719 P1000719 0000 0.9282932 0000 0.9927706 0.0005653600
#> 720 P1000720 1001 0.6775810 0001 0.4643624 0.2432816314
#> 721 P1000721 0010 0.8998024 0010 0.9650171 0.0018692537
#> 722 P1000722 1110 0.8903084 1110 0.7029903 0.9708285202
#> 723 P1000723 1001 0.8457611 1001 0.6344224 0.9485747024
#> 724 P1000724 0000 0.8872653 0000 0.9825946 0.0005613861
#> 725 P1000725 0000 0.6470421 0000 0.9289599 0.0005454399
#> 726 P1000726 1001 0.5271034 0001 0.4403920 0.0663557087
#> 727 P1000727 0000 0.7293857 0000 0.9758475 0.0038118734
#> 728 P1000728 1111 0.9811121 1111 0.9968864 0.9984810816
#> 729 P1000729 0000 0.7080554 0000 0.9866667 0.0067102673
#> 730 P1000730 0001 0.7649721 0000 0.8049462 0.0005792785
#> 731 P1000731 0000 0.9282932 0000 0.9927706 0.0005653600
#> 732 P1000732 0010 0.7525064 0010 0.8447209 0.0024160546
#> 733 P1000733 1000 0.6642869 0000 0.7112746 0.2145021785
#> 734 P1000734 0000 0.6787328 0000 0.9423833 0.0005508845
#> 735 P1000735 0010 0.5036036 0000 0.7902812 0.0018213039
#> 736 P1000736 0000 0.4962052 0000 0.9500985 0.0067120927
#> 737 P1000737 0000 0.7964507 0000 0.9679898 0.0018112151
#> 738 P1000738 0001 0.8246897 0001 0.4964776 0.0061530588
#> 739 P1000739 0000 0.3983603 0000 0.9263338 0.0067300128
#> 740 P1000740 1111 0.8651588 1111 0.9667779 0.9984783630
#> 741 P1000741 0110 0.6113799 0110 0.4583380 0.0003556592
#> 742 P1000742 0110 0.4780191 0010 0.5442421 0.0001810192
#> 743 P1000743 1111 0.9338170 1111 0.9875029 0.9984446664
#> 744 P1000744 0000 0.6804043 0000 0.9624649 0.0008006940
#> 745 P1000745 0101 0.9502877 0101 0.9317083 0.0073820397
#> 746 P1000746 1111 0.7880733 1111 0.9895554 0.9985633055
#> 747 P1000747 1110 0.6247183 1110 0.5240782 0.6455275019
#> 748 P1000748 1010 0.6356015 0010 0.6714742 0.2409280676
#> 749 P1000749 0001 0.6860807 0000 0.8059173 0.0008405061
#> 750 P1000750 1000 0.6682169 0000 0.9461917 0.0439961939
#> 751 P1000751 0100 0.3638373 0000 0.8619452 0.0162202378
#> 752 P1000752 0000 0.8927890 0000 0.9898609 0.0005653722
#> 753 P1000753 1111 0.6807760 1111 0.8346416 0.8387170822
#> 754 P1000754 0000 0.5348349 0000 0.9586757 0.0067116646
#> 755 P1000755 1000 0.8911317 0000 0.7654173 0.2080591229
#> 756 P1000756 0010 0.4361013 0000 0.7932763 0.0057892728
#> 757 P1000757 0100 0.3116120 0100 0.6021164 0.0646808229
#> 758 P1000758 1110 0.6535106 1111 0.7085078 0.9998277996
#> 759 P1000759 1000 0.7285287 0000 0.9062972 0.0725219142
#> 760 P1000760 0000 0.7964507 0000 0.9679898 0.0018112151
#> 761 P1000761 0010 0.3567183 0000 0.6255816 0.0131202965
#> 762 P1000762 0000 0.5468626 0000 0.9116578 0.0063674844
#> 763 P1000763 0010 0.8195020 0010 0.7330043 0.0021381355
#> 764 P1000764 0111 0.5590021 0111 0.7730528 0.0213586524
#> 765 P1000765 1010 0.8672077 1010 0.8294412 0.9978798275
#> 766 P1000766 0000 0.9282932 0000 0.9927706 0.0005653600
#> 767 P1000767 1111 0.9838947 1111 0.9982173 0.9998720377
#> 768 P1000768 0000 0.8743368 0000 0.9882626 0.0005653790
#> 769 P1000769 0000 0.5800606 0000 0.9046546 0.0008683551
#> 770 P1000770 0000 0.9282932 0000 0.9927706 0.0005653600
#> 771 P1000771 0000 0.5785747 0000 0.9191098 0.0005459594
#> 772 P1000772 0010 0.6702493 0000 0.5616826 0.0015520367
#> 773 P1000773 1010 0.8208440 1010 0.8300784 0.9721731823
#> 774 P1000774 0001 0.4005422 0001 0.4181136 0.0227895955
#> 775 P1000775 0111 0.9645253 0111 0.9759722 0.0029310391
#> 776 P1000776 0100 0.6794738 0000 0.8472275 0.0005661125
#> 777 P1000777 1111 0.9360058 1111 0.9789632 0.9817572972
#> 778 P1000778 1000 0.4287573 0000 0.8928755 0.0487436587
#> 779 P1000779 0000 0.8743368 0000 0.9882626 0.0005653790
#> 780 P1000780 0110 0.5357517 0110 0.5025473 0.0259116528
#> 781 P1000781 0000 0.7300813 0000 0.9602715 0.0008237620
#> 782 P1000782 1111 0.9773416 1111 0.9959061 0.9982968479
#> 783 P1000783 1000 0.5057397 0000 0.9482153 0.0222025561
#> 784 P1000784 0000 0.7155833 0000 0.9732810 0.0005668043
#> 785 P1000785 1111 0.9866593 1111 0.9965154 0.9984845732
#> 786 P1000786 0000 0.5539239 0000 0.9217792 0.0005504543
#> 787 P1000787 0000 0.4902297 0000 0.9489688 0.0065064802
#> 788 P1000788 0011 0.5343819 0010 0.7061714 0.0024798933
#> 789 P1000789 1100 0.8895724 1100 0.8334613 0.9958136618
#> 790 P1000790 0111 0.8183390 0111 0.6905889 0.3034068323
#> 791 P1000791 0010 0.6940056 0010 0.4933258 0.0018428294
#> 792 P1000792 0000 0.8500130 0000 0.9863794 0.0005655706
#> 793 P1000793 0100 0.5055338 0100 0.7434630 0.0060974692
#> 794 P1000794 0000 0.6975588 0000 0.9200437 0.0005362753
#> 795 P1000795 1110 0.8444039 1110 0.7303626 0.9960896851
#> 796 P1000796 0011 0.7324954 0011 0.7156392 0.0272634786
#> 797 P1000797 0000 0.7537781 0000 0.9500998 0.0005500468
#> 798 P1000798 0000 0.4580857 0000 0.8962556 0.0066858593
#> 799 P1000799 0000 0.7080554 0000 0.9866667 0.0067102673
#> 800 P1000800 0011 0.5095948 0011 0.6523477 0.2877183714
#> 801 P1000801 0010 0.7507007 0010 0.9427481 0.0278892560
#> 802 P1000802 0010 0.9064654 0010 0.9413896 0.0018673940
#> 803 P1000803 1000 0.7052402 1000 0.6718765 0.9561223542
#> 804 P1000804 1000 0.4688084 0000 0.5406614 0.0543623619
#> 805 P1000805 0010 0.5818501 0010 0.7956679 0.0077379735
#> 806 P1000806 0000 0.6082734 0000 0.9708370 0.0091647807
#> 807 P1000807 1111 0.7358549 1111 0.9638576 0.9986660382
#> 808 P1000808 0000 0.7361847 0000 0.9756201 0.0005666309
#> 809 P1000809 0000 0.5675920 0000 0.9148579 0.0061696961
#> 810 P1000810 0001 0.6411735 0001 0.4512001 0.0006039048
#> 811 P1000811 0010 0.8664862 0010 0.9552670 0.0025696422
#> 812 P1000812 0100 0.4638348 0000 0.6417334 0.0265402448
#> 813 P1000813 0000 0.6989708 0000 0.9711226 0.0005666553
#> 814 P1000814 1000 0.4416602 0000 0.9372252 0.0212440998
#> 815 P1000815 0000 0.7117645 0000 0.9727170 0.0005666466
#> 816 P1000816 1000 0.8076813 0000 0.9159021 0.0779498286
#> 817 P1000817 0000 0.4361474 0000 0.9347999 0.0040780180
#> 818 P1000818 0111 0.9296249 0111 0.9602132 0.0023913674
#> 819 P1000819 0001 0.7484117 0000 0.6146251 0.0053947465
#> 820 P1000820 0000 0.6491560 0000 0.9141575 0.0005364903
#> 821 P1000821 0000 0.7945936 0000 0.9543939 0.0005500125
#> 822 P1000822 0000 0.6549616 0000 0.9392131 0.0005509128
#> 823 P1000823 0000 0.9282932 0000 0.9927706 0.0005653600
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#> 825 P1000825 0000 0.6993881 0000 0.9863499 0.0070291677
#> 826 P1000826 0010 0.4174341 0000 0.7727544 0.0011389529
#> 827 P1000827 1111 0.8082649 1111 0.9695062 0.9982954196
#> 828 P1000828 0010 0.6892591 0000 0.6501465 0.0004283389
#> 829 P1000829 1000 0.3677150 0000 0.7160118 0.0326954601
#> 830 P1000830 1111 0.6708758 1111 0.8198124 0.8200536722
#> 831 P1000831 1111 0.9059556 1111 0.9774433 0.9984487180
#> 832 P1000832 1110 0.5335360 1111 0.6809776 0.9735681869
#> 833 P1000833 0000 0.7138207 0000 0.9868733 0.0065023196
#> 834 P1000834 0111 0.9139912 0111 0.9168102 0.0301621212
#> 835 P1000835 1000 0.5893154 0000 0.6176272 0.0864749086
#> 836 P1000836 0000 0.7193428 0000 0.9814456 0.0038389835
#> 837 P1000837 1111 0.8620459 1111 0.9678265 0.9998679201
#> 838 P1000838 1111 0.9598263 1111 0.9825032 0.9827684581
#> 839 P1000839 1111 0.4217841 1111 0.6973649 0.8034086967
#> 840 P1000840 0010 0.3160926 0000 0.7605720 0.0034670918
#> 841 P1000841 1001 0.5678210 0001 0.6700543 0.0832416492
#> 842 P1000842 1111 0.8583916 1111 0.9668388 0.9998672207
#> 843 P1000843 0000 0.8309927 0000 0.9778750 0.0007988070
#> 844 P1000844 0100 0.4159585 0000 0.7059003 0.0011338678
#> 845 P1000845 1111 0.8650316 1111 0.9666492 0.9984288796
#> 846 P1000846 0100 0.6129824 0000 0.8351336 0.0022208486
#> 847 P1000847 1111 0.9327810 1111 0.9788512 0.9825002607
#> 848 P1000848 0000 0.7576885 0000 0.9859370 0.0038387685
#> 849 P1000849 0000 0.7359227 0000 0.9617702 0.0018118864
#> 850 P1000850 1111 0.9037831 1111 0.9773618 0.9986427319
#> 851 P1000851 0000 0.7565539 0000 0.9766102 0.0005655825
#> 852 P1000852 0000 0.4527370 0000 0.8297501 0.0010543841
#> 853 P1000853 1111 0.8869433 1111 0.9746018 0.9985525938
#> 854 P1000854 0000 0.8927890 0000 0.9898609 0.0005653722
#> 855 P1000855 0000 0.9282932 0000 0.9927706 0.0005653600
#> 856 P1000856 1000 0.6439497 0000 0.8648981 0.0747075840
#> 857 P1000857 0000 0.5978045 0000 0.9546433 0.0005657239
#> 858 P1000858 0000 0.4852453 0000 0.8852378 0.0005368399
#> 859 P1000859 0010 0.7026147 0010 0.8863573 0.0273941421
#> 860 P1000860 0000 0.8800457 0000 0.9823247 0.0007988135
#> 861 P1000861 1010 0.9292315 1010 0.7600233 0.8062053541
#> 862 P1000862 1011 0.6112086 1011 0.8852585 0.9972240968
#> 863 P1000863 1011 0.9084012 1011 0.8085071 0.9829786709
#> 864 P1000864 0100 0.3576982 0000 0.6895131 0.0004912674
#> 865 P1000865 0000 0.7193428 0000 0.9814456 0.0038389835
#> 866 P1000866 0000 0.5070868 0000 0.9528797 0.0065062629
#> 867 P1000867 0010 0.7897240 0010 0.8297953 0.0227605589
#> 868 P1000868 0010 0.7273216 0000 0.4988601 0.0003702594
#> 869 P1000869 0110 0.9375559 0110 0.9454457 0.0022885018
#> 870 P1000870 0000 0.9282932 0000 0.9927706 0.0005653600
#> 871 P1000871 1010 0.7134292 0010 0.7260240 0.2636864183
#> 872 P1000872 0000 0.7361847 0000 0.9756201 0.0005666309
#> 873 P1000873 0010 0.7629647 0010 0.9466223 0.0279380051
#> 874 P1000874 0000 0.6129665 0000 0.9604363 0.0008986971
#> 875 P1000875 0010 0.3188115 0000 0.7714894 0.0213262782
#> 876 P1000876 0111 0.9452770 0111 0.9818684 0.0021220687
#> 877 P1000877 1111 0.7950505 1111 0.9881727 0.9980463956
#> 878 P1000878 0000 0.6096313 0000 0.9122609 0.0046029849
#> 879 P1000879 0000 0.6989708 0000 0.9711226 0.0005666553
#> 880 P1000880 0111 0.5097944 0111 0.5594361 0.0016119671
#> 881 P1000881 0000 0.7481017 0000 0.9615633 0.0005571424
#> 882 P1000882 0010 0.8594290 0010 0.6860286 0.0020286885
#> 883 P1000883 0011 0.3439814 0111 0.4568351 0.3032421732
#> 884 P1000884 0000 0.4167322 0000 0.8617809 0.0117091144
#> 885 P1000885 0111 0.7478306 0111 0.6898186 0.2860677632
#> 886 P1000886 0001 0.9023619 0001 0.8386370 0.0006151855
#> 887 P1000887 0010 0.6230747 0000 0.6471134 0.0050915492
#> 888 P1000888 0101 0.3874928 0111 0.5108271 0.0002905953
#> 889 P1000889 1000 0.7954531 0000 0.9132162 0.0779513853
#> 890 P1000890 0000 0.9282932 0000 0.9927706 0.0005653600
#> 891 P1000891 0001 0.4947287 0000 0.7215062 0.0018559563
#> 892 P1000892 0000 0.7576885 0000 0.9859370 0.0038387685
#> 893 P1000893 0100 0.8732978 0100 0.5385926 0.0036041765
#> 894 P1000894 1000 0.4346793 0000 0.9317361 0.0222518054
#> 895 P1000895 0000 0.5905408 0000 0.8767153 0.0009908226
#> 896 P1000896 0000 0.9282932 0000 0.9927706 0.0005653600
#> 897 P1000897 0010 0.4992733 0010 0.8137896 0.0019068834
#> 898 P1000898 1110 0.4764513 1110 0.5228087 0.9912367932
#> 899 P1000899 0000 0.6885021 0000 0.9632729 0.0005628098
#> 900 P1000900 1111 0.9642037 1111 0.9945124 0.9986750553
#> 901 P1000901 0111 0.9289346 0111 0.9688395 0.0001937527
#> 902 P1000902 1010 0.8659547 1010 0.6788962 0.7299487929
#> 903 P1000903 1000 0.7360498 0000 0.9031623 0.0757300067
#> 904 P1000904 0000 0.9020697 0000 0.9914361 0.0008358458
#> 905 P1000905 0000 0.6654502 0000 0.9646077 0.0005654785
#> 906 P1000906 0000 0.7080554 0000 0.9866667 0.0067102673
#> 907 P1000907 0000 0.5347872 0000 0.9309935 0.0018123124
#> 908 P1000908 0100 0.6625230 0000 0.6494121 0.0024178087
#> 909 P1000909 1111 0.9941190 1111 0.9982281 0.9984870134
#> 910 P1000910 0000 0.9282932 0000 0.9927706 0.0005653600
#> 911 P1000911 0000 0.8878243 0000 0.9894369 0.0005653740
#> 912 P1000912 0000 0.7945936 0000 0.9543939 0.0005500125
#> 913 P1000913 0000 0.5468626 0000 0.9116578 0.0063674844
#> 914 P1000914 0000 0.5932980 0000 0.9138313 0.0036418719
#> 915 P1000915 0110 0.4764084 0110 0.4453690 0.1979600290
#> 916 P1000916 1100 0.8762272 1100 0.4937123 0.9945372906
#> 917 P1000917 0100 0.8591474 0100 0.5899983 0.0039074917
#> 918 P1000918 0010 0.7351365 0010 0.7794779 0.0233041669
#> 919 P1000919 0000 0.9282932 0000 0.9927706 0.0005653600
#> 920 P1000920 1001 0.4324221 0001 0.4982948 0.0676204347
#> 921 P1000921 0000 0.3512104 0000 0.8221457 0.0130380935
#> 922 P1000922 0000 0.5638893 0000 0.9146762 0.0063670745
#> 923 P1000923 0011 0.6461754 0011 0.4470079 0.0112008609
#> 924 P1000924 0011 0.5770077 0011 0.4700397 0.0133360802
#> 925 P1000925 1111 0.9548360 1111 0.9820406 0.9839271454
#> 926 P1000926 0000 0.7540634 0000 0.9408216 0.0005445847
#> 927 P1000927 0000 0.7200332 0000 0.9583250 0.0005571652
#> 928 P1000928 1010 0.5929871 0010 0.3741950 0.2411221334
#> 929 P1000929 0110 0.3881979 0111 0.4122674 0.0249640284
#> 930 P1000930 1111 0.8164891 1111 0.9566707 0.9998647430
#> 931 P1000931 0000 0.9282932 0000 0.9927706 0.0005653600
#> 932 P1000932 1111 0.9702778 1111 0.9953689 0.9983953998
#> 933 P1000933 1110 0.4777458 1110 0.5615966 0.9691311339
#> 934 P1000934 1111 0.6480532 1111 0.9207238 0.9837644879
#> 935 P1000935 0010 0.6574088 0010 0.8346857 0.0423681269
#> 936 P1000936 0000 0.7325251 0000 0.9830379 0.0038389073
#> 937 P1000937 0101 0.7475752 0101 0.5549036 0.0077833654
#> 938 P1000938 1111 0.7656652 1111 0.9737267 0.9823426469
#> 939 P1000939 0010 0.7369208 0010 0.9193584 0.0274205216
#> 940 P1000940 0011 0.4248609 0010 0.5642888 0.0215484523
#> 941 P1000941 0010 0.7345548 0000 0.5668334 0.0015540192
#> 942 P1000942 0010 0.3698104 0000 0.7600576 0.0008240283
#> 943 P1000943 0000 0.7565539 0000 0.9766102 0.0005655825
#> 944 P1000944 0100 0.5548431 0000 0.8293206 0.0013858738
#> 945 P1000945 0110 0.9468729 0110 0.9148369 0.0001706061
#> 946 P1000946 0000 0.9020697 0000 0.9914361 0.0008358458
#> 947 P1000947 1111 0.4192301 1111 0.7943164 0.9692845181
#> 948 P1000948 0000 0.7155833 0000 0.9732810 0.0005668043
#> 949 P1000949 0001 0.7816691 0000 0.6654463 0.0005771856
#> 950 P1000950 1000 0.6579908 0000 0.9367735 0.0437002905
#> 951 P1000951 0000 0.3761596 0000 0.8608793 0.0180104829
#> 952 P1000952 0011 0.8089118 0011 0.7427845 0.0027719419
#> 953 P1000953 0100 0.9027894 0100 0.6131801 0.0005689384
#> 954 P1000954 0001 0.4315006 0000 0.8807375 0.0040507759
#> 955 P1000955 0000 0.6215984 0000 0.9121439 0.0005372676
#> 956 P1000956 0000 0.5902171 0000 0.9072086 0.0007941461
#> 957 P1000957 0000 0.6975588 0000 0.9200437 0.0005362753
#> 958 P1000958 1111 0.9789862 1111 0.9977218 0.9998724183
#> 959 P1000959 1111 0.9877654 1111 0.9967845 0.9985321715
#> 960 P1000960 0000 0.9282932 0000 0.9927706 0.0005653600
#> 961 P1000961 1110 0.6483400 1111 0.7062299 0.9979928789
#> 962 P1000962 0000 0.5445402 0000 0.9107753 0.0061702333
#> 963 P1000963 0010 0.6143040 0000 0.6398793 0.0004289690
#> 964 P1000964 0001 0.7850017 0000 0.7853981 0.0005807271
#> 965 P1000965 0101 0.6719850 0101 0.3806610 0.0076672511
#> 966 P1000966 0010 0.8862591 0010 0.8301469 0.0002309276
#> 967 P1000967 0000 0.7117645 0000 0.9727170 0.0005666466
#> 968 P1000968 0111 0.7139610 0111 0.7760184 0.0242355932
#> 969 P1000969 0000 0.5212701 0000 0.9421989 0.0010777585
#> 970 P1000970 0110 0.6795218 0110 0.7649210 0.1840290991
#> 971 P1000971 0000 0.8800457 0000 0.9823247 0.0007988135
#> 972 P1000972 1101 0.7784202 1111 0.8842568 0.9997171357
#> 973 P1000973 0010 0.6940056 0010 0.4933258 0.0018428294
#> 974 P1000974 0000 0.5912252 0000 0.9709972 0.0067213307
#> 975 P1000975 0000 0.7481017 0000 0.9615633 0.0005571424
#> 976 P1000976 0000 0.5259698 0000 0.8428973 0.0010523073
#> 977 P1000977 1111 0.9544796 1111 0.9810086 0.9819315031
#> 978 P1000978 0000 0.4178932 0000 0.9061062 0.0005591313
#> 979 P1000979 0010 0.6304870 0010 0.5594970 0.0207831671
#> 980 P1000980 1000 0.6497798 1000 0.7443040 0.8678010479
#> 981 P1000981 0001 0.6728006 0000 0.8232751 0.0005665587
#> 982 P1000982 1111 0.5872173 1111 0.8679200 0.9998525942
#> 983 P1000983 0001 0.6953883 0000 0.8071269 0.0005676583
#> 984 P1000984 0110 0.5735777 0110 0.5505366 0.1782432855
#> 985 P1000985 0000 0.7540634 0000 0.9408216 0.0005445847
#> 986 P1000986 0100 0.7789881 0000 0.6129656 0.0005452231
#> 987 P1000987 0110 0.9791692 0110 0.9741184 0.0018823485
#> 988 P1000988 1111 0.9287272 1111 0.9776399 0.9811303775
#> 989 P1000989 0000 0.5923462 0000 0.9557367 0.0066133234
#> 990 P1000990 0001 0.6098091 0000 0.8023130 0.0065285947
#> 991 P1000991 0101 0.9155589 0101 0.7999032 0.0006319023
#> 992 P1000992 0000 0.7234958 0000 0.9587369 0.0005571623
#> 993 P1000993 1111 0.3807391 1111 0.8306354 0.9973371810
#> 994 P1000994 0101 0.6712957 0101 0.4284992 0.0006175669
#> 995 P1000995 0000 0.6754253 0000 0.9762841 0.0069800770
#> 996 P1000996 0010 0.8862591 0010 0.8301469 0.0002309276
#> 997 P1000997 0100 0.7907016 0100 0.8593407 0.0041566469
#> 998 P1000998 0000 0.6993881 0000 0.9863499 0.0070291677
#> 999 P1000999 0100 0.4000176 0000 0.4189349 0.0057324173
#> 1000 P1001000 0010 0.6621689 0000 0.5672144 0.0069611236
#> post.attr2 post.attr3 post.attr4
#> 1 0.6514881225 0.035150582 0.971302786
#> 2 0.0107672033 0.999794858 0.936926366
#> 3 0.9828893114 0.626429305 0.978044317
#> 4 0.0004327554 0.005121344 0.001098307
#> 5 0.0006620112 0.314809026 0.741864979
#> 6 0.2925355687 0.250887856 0.003257354
#> 7 0.9579821075 0.999944997 0.039302741
#> 8 0.0392505038 0.754486183 0.020909895
#> 9 0.0122348973 0.005365168 0.833024605
#> 10 0.0050263779 0.005147985 0.013656279
#> 11 0.0110318711 0.925242689 0.946173669
#> 12 0.9973208904 0.953250807 0.999894378
#> 13 0.0752470910 0.016476126 0.495270510
#> 14 0.9996203258 0.999533548 0.996232497
#> 15 0.0004316733 0.015412189 0.001098978
#> 16 0.5805682511 0.004564928 0.218812044
#> 17 0.0050266399 0.005126476 0.013666705
#> 18 0.0046697940 0.005326803 0.265216218
#> 19 0.0716549320 0.944097299 0.069248065
#> 20 0.0033944921 0.028817597 0.018462449
#> 21 0.0112500811 0.998338107 0.798491762
#> 22 0.9989476380 0.798364751 0.999756340
#> 23 0.9998172518 0.999908556 0.703196331
#> 24 0.0007664296 0.015078296 0.004743039
#> 25 0.5310478620 0.004502870 0.014178583
#> 26 0.9999798484 0.999996582 0.704236024
#> 27 0.4818204100 0.265695299 0.027032460
#> 28 0.0033623759 0.005141124 0.001100228
#> 29 0.0059236066 0.015704243 0.001104422
#> 30 0.0004287568 0.043602023 0.001103228
#> 31 0.9998400341 0.998731563 0.019121267
#> 32 0.9986735326 0.991982788 0.019080775
#> 33 0.0116773757 0.005129836 0.001108355
#> 34 0.0003995357 0.326628131 0.001149393
#> 35 0.9996209721 0.999503294 0.999781328
#> 36 0.1837032216 0.517483381 0.001375255
#> 37 0.9372335378 0.991516701 0.997590679
#> 38 0.9953242523 0.999863189 0.904886892
#> 39 0.9980413508 0.999455482 0.999868079
#> 40 0.0033541008 0.015699948 0.001103117
#> 41 0.9992947201 0.999774199 0.124417905
#> 42 0.0015391137 0.028812331 0.013663068
#> 43 0.0004302944 0.028770488 0.001101155
#> 44 0.0037545614 0.043568550 0.001106466
#> 45 0.0003552849 0.753937675 0.001211446
#> 46 0.0055473763 0.805580424 0.015018691
#> 47 0.0004327347 0.005144710 0.001097383
#> 48 0.0005344310 0.354991114 0.400078195
#> 49 0.0037002691 0.138987274 0.011157900
#> 50 0.0003309124 0.995020166 0.001290839
#> 51 0.8222996979 0.341358730 0.089164145
#> 52 0.0065666033 0.003516099 0.123597062
#> 53 0.0096496368 0.164759328 0.556679067
#> 54 0.0003973349 0.347501435 0.001150100
#> 55 0.0066735177 0.015791354 0.001105177
#> 56 0.0548884191 0.003421891 0.130209098
#> 57 0.0047004052 0.005170578 0.045029182
#> 58 0.0035264711 0.005167316 0.056494154
#> 59 0.0004172187 0.155160763 0.001120270
#> 60 0.8210883657 0.926850256 0.012676475
#> 61 0.0028335300 0.353262285 0.021734558
#> 62 0.0949190915 0.005312099 0.442994491
#> 63 0.0004375259 0.005153585 0.013602339
#> 64 0.1199545223 0.015012594 0.001215415
#> 65 0.0040126648 0.042642021 0.078640642
#> 66 0.0049715865 0.005139155 0.001101790
#> 67 0.0075080884 0.631546839 0.446514055
#> 68 0.1228691608 0.772503439 0.001348929
#> 69 0.0037894502 0.005118406 0.001101523
#> 70 0.1141353517 0.015002904 0.003275838
#> 71 0.0014998142 0.043583331 0.001104309
#> 72 0.9790100408 0.550624463 0.998785358
#> 73 0.6164196684 0.004270095 0.009412167
#> 74 0.8617404371 0.976770213 0.015189089
#> 75 0.0033625360 0.005117774 0.001101154
#> 76 0.2641415400 0.815633585 0.001515755
#> 77 0.9978175645 0.999885043 0.999877743
#> 78 0.0042522010 0.028935620 0.003856107
#> 79 0.1066486444 0.246647996 0.047467586
#> 80 0.0004393716 0.005134644 0.018368320
#> 81 0.0015300122 0.015447732 0.013635446
#> 82 0.0004287568 0.043602023 0.001103228
#> 83 0.0138617920 0.207926610 0.128264875
#> 84 0.0014135157 0.326442818 0.001147583
#> 85 0.0004341389 0.005135443 0.004735277
#> 86 0.0035610824 0.257761509 0.001139133
#> 87 0.0074604279 0.999437092 0.135821139
#> 88 0.0042696555 0.005141882 0.003742391
#> 89 0.0033577962 0.057023526 0.013743694
#> 90 0.0004878402 0.029524625 0.152793782
#> 91 0.0038671441 0.979460311 0.015987385
#> 92 0.0004327347 0.005144710 0.001097383
#> 93 0.7711427590 0.999867956 0.998577064
#> 94 0.0442458508 0.093342606 0.011354251
#> 95 0.0004327554 0.005121344 0.001098307
#> 96 0.0321635607 0.028584389 0.004020813
#> 97 0.0004327537 0.005123248 0.001098231
#> 98 0.9998659939 0.999799576 0.983886322
#> 99 0.0015287237 0.756264129 0.022944102
#> 100 0.1254409452 0.004989791 0.083778903
#> 101 0.1001598130 0.076850545 0.060112586
#> 102 0.0154105310 0.088480054 0.158407186
#> 103 0.0032478130 0.431723782 0.001165548
#> 104 0.9862049508 0.064943980 0.996848636
#> 105 0.0117746013 0.997553885 0.725282368
#> 106 0.2360151619 0.999851003 0.982093958
#> 107 0.0004327347 0.005144710 0.001097383
#> 108 0.5016234162 0.004532244 0.003025511
#> 109 0.4192228058 0.409227585 0.014320690
#> 110 0.1964796333 0.005230506 0.500204086
#> 111 0.1611066397 0.032819530 0.001263898
#> 112 0.0484555732 0.005125794 0.060127373
#> 113 0.0059208529 0.015637159 0.001105288
#> 114 0.0047010074 0.005146968 0.045065435
#> 115 0.0015831537 0.152498734 0.001121040
#> 116 0.9338266759 0.982769844 0.003124589
#> 117 0.9997979368 0.985024538 0.978875924
#> 118 0.1232702337 0.686751079 0.043077585
#> 119 0.9956085597 0.999513981 0.983908365
#> 120 0.3025252381 0.014322423 0.006479347
#> 121 0.0042696555 0.005141882 0.003742391
#> 122 0.0004391751 0.015743694 0.020760070
#> 123 0.9999847570 0.999997677 0.998744895
#> 124 0.0007640737 0.015104901 0.001099232
#> 125 0.6188543438 0.094335612 0.626129668
#> 126 0.0039741251 0.005166776 0.056514259
#> 127 0.0049718037 0.005117715 0.001102642
#> 128 0.5805986273 0.004725571 0.514591198
#> 129 0.0042696555 0.005141882 0.003742391
#> 130 0.0044034584 0.497495405 0.005066022
#> 131 0.0039741251 0.005166776 0.056514259
#> 132 0.8155705379 0.501469482 0.496751466
#> 133 0.0003926299 0.593762221 0.064929376
#> 134 0.0004339940 0.027428861 0.010485774
#> 135 0.0052274924 0.747029115 0.022884601
#> 136 0.0030260108 0.850443158 0.001232108
#> 137 0.9995929278 0.882828666 0.997895809
#> 138 0.9998669481 0.999763084 0.998746778
#> 139 0.0006075294 0.034044692 0.468991565
#> 140 0.0037574936 0.055580616 0.004996541
#> 141 0.0038002683 0.027407611 0.010516239
#> 142 0.1028350570 0.951235936 0.046581851
#> 143 0.0003615786 0.693093884 0.001202228
#> 144 0.0004287568 0.043602023 0.001103228
#> 145 0.0004362205 0.043715398 0.020815522
#> 146 0.1447425658 0.015180384 0.003260201
#> 147 0.0047009583 0.005148892 0.045062480
#> 148 0.0004043931 0.315783586 0.012137482
#> 149 0.9997400062 0.999281554 0.974578751
#> 150 0.0004375488 0.005132053 0.013612721
#> 151 0.0004341389 0.005135443 0.004735277
#> 152 0.9941907823 0.921915739 0.966559354
#> 153 0.9840654665 0.998672075 0.015642861
#> 154 0.0970098072 0.070306144 0.004662115
#> 155 0.0420529660 0.005093769 0.001137795
#> 156 0.9005981452 0.425993943 0.012678269
#> 157 0.0043581121 0.043550124 0.016088010
#> 158 0.0144873023 0.005129086 0.003334373
#> 159 0.0012578294 0.744624199 0.014605174
#> 160 0.9989420622 0.999657256 0.976367388
#> 161 0.9994044180 0.936770715 0.981245130
#> 162 0.9998021091 0.999711742 0.967644377
#> 163 0.0004375508 0.005130142 0.013613643
#> 164 0.0003875442 0.463360263 0.001303448
#> 165 0.0034792501 0.348305995 0.001152652
#> 166 0.0004327347 0.005144710 0.001097383
#> 167 0.0004327554 0.005121344 0.001098307
#> 168 0.0004316733 0.015412189 0.001098978
#> 169 0.0089374720 0.083785764 0.001121087
#> 170 0.0356984442 0.077434922 0.004069490
#> 171 0.0004251962 0.078024342 0.001108460
#> 172 0.0003494467 0.810379097 0.001220030
#> 173 0.0004043931 0.315783586 0.012137482
#> 174 0.0003511587 0.811079602 0.006071978
#> 175 0.7028700665 0.975157325 0.131834896
#> 176 0.0004252474 0.077695822 0.001109293
#> 177 0.0380141017 0.015317518 0.021400772
#> 178 0.8498366038 0.999932323 0.996926863
#> 179 0.0004323209 0.028903109 0.005497262
#> 180 0.9758602689 0.999954998 0.999856862
#> 181 0.0409487426 0.028648822 0.120820182
#> 182 0.0374774217 0.005099369 0.001133352
#> 183 0.9997601359 0.999972186 0.969241873
#> 184 0.2269682625 0.004849843 0.005784438
#> 185 0.0309122825 0.052457016 0.003345154
#> 186 0.1332551331 0.004979352 0.001226573
#> 187 0.0003345340 0.996356418 0.016039338
#> 188 0.0066704177 0.015723904 0.001106042
#> 189 0.0065751552 0.881899142 0.767419342
#> 190 0.0004329822 0.004864971 0.001108440
#> 191 0.0004353248 0.043701792 0.018449953
#> 192 0.9998926342 0.999918587 0.981922014
#> 193 0.9804897338 0.993316725 0.975261146
#> 194 0.0003700878 0.656156601 0.014480984
#> 195 0.9967122842 0.999997256 0.998721228
#> 196 0.0004327347 0.005144710 0.001097383
#> 197 0.0007640737 0.015104901 0.001099232
#> 198 0.0037892787 0.005140602 0.001100642
#> 199 0.7638472019 0.250032738 0.002952527
#> 200 0.0004251962 0.078024342 0.001108460
#> 201 0.0004327544 0.005122497 0.001098261
#> 202 0.0004302944 0.028770488 0.001101155
#> 203 0.0852529758 0.005693221 0.983214048
#> 204 0.0061996794 0.926870893 0.001244224
#> 205 0.0016192659 0.005122843 0.018393816
#> 206 0.9928243964 0.996825692 0.121420826
#> 207 0.8303844369 0.999941393 0.030083082
#> 208 0.0004393464 0.005156957 0.018353890
#> 209 0.0004327347 0.005144710 0.001097383
#> 210 0.0034135957 0.005153331 0.018400642
#> 211 0.9985786813 0.995444966 0.811492512
#> 212 0.5775345457 0.051057418 0.219653855
#> 213 0.0004316733 0.015412189 0.001098978
#> 214 0.0033434700 0.028750912 0.001103989
#> 215 0.8568559135 0.114697044 0.011735840
#> 216 0.9543366531 0.984618252 0.003110685
#> 217 0.4064608232 0.998514099 0.021666079
#> 218 0.7872143956 0.983795310 0.998508226
#> 219 0.0099863165 0.005522718 0.551676865
#> 220 0.1020761106 0.159698463 0.447427177
#> 221 0.6667380106 0.092627765 0.015131867
#> 222 0.0004327537 0.005123248 0.001098231
#> 223 0.0004287923 0.043421009 0.001104060
#> 224 0.0049104914 0.056898217 0.001110526
#> 225 0.8300360517 0.455736729 0.695928000
#> 226 0.9659006044 0.996916692 0.959799695
#> 227 0.0852648448 0.421644065 0.001247308
#> 228 0.0004391920 0.018874955 0.021009969
#> 229 0.9999847635 0.999979539 0.999899894
#> 230 0.2168672624 0.041053854 0.176582661
#> 231 0.9998236154 0.999716776 0.998694699
#> 232 0.9542430116 0.029724128 0.901317614
#> 233 0.0385027306 0.609998139 0.216053487
#> 234 0.0724588650 0.938916929 0.473968701
#> 235 0.0004327347 0.005144710 0.001097383
#> 236 0.0073879300 0.928734716 0.213504787
#> 237 0.0004317288 0.028793874 0.004798770
#> 238 0.0047948825 0.688342598 0.005190535
#> 239 0.0017672247 0.005276298 0.190234864
#> 240 0.6118010633 0.228549265 0.015105574
#> 241 0.9878861144 0.999726081 0.968051948
#> 242 0.0115700296 0.043480823 0.001114126
#> 243 0.9973433094 0.999971715 0.865711313
#> 244 0.1809429203 0.344210511 0.396711413
#> 245 0.1226157445 0.131945893 0.191503780
#> 246 0.0030626086 0.850588343 0.015211008
#> 247 0.5057091182 0.004917703 0.681216650
#> 248 0.0081795509 0.880542848 0.011479573
#> 249 0.9926647309 0.826256776 0.982354893
#> 250 0.0033241696 0.998887021 0.170786969
#> 251 0.0003462741 0.897290110 0.020583215
#> 252 0.0049715865 0.005139155 0.001101790
#> 253 0.0099863165 0.005522718 0.551676865
#> 254 0.0030530617 0.444315905 0.010676707
#> 255 0.9419871469 0.711005194 0.440208319
#> 256 0.0323368104 0.005085576 0.004002384
#> 257 0.0451730968 0.902655014 0.001283647
#> 258 0.0251456300 0.018028044 0.040287906
#> 259 0.0004339028 0.057331819 0.018483923
#> 260 0.0137427319 0.199678245 0.034134915
#> 261 0.0037892787 0.005140602 0.001100642
#> 262 0.0132172917 0.028685436 0.001113773
#> 263 0.0038336957 0.004869045 0.013777966
#> 264 0.0561093714 0.757775686 0.001273144
#> 265 0.0060706478 0.045069492 0.266448663
#> 266 0.5862645329 0.741884906 0.770755045
#> 267 0.0084525472 0.033255998 0.410849000
#> 268 0.0471545245 0.005089564 0.004134768
#> 269 0.0098826707 0.687728109 0.994283058
#> 270 0.7783991269 0.821924163 0.328923194
#> 271 0.2440972932 0.973435102 0.269798984
#> 272 0.9998069322 0.999955539 0.998039550
#> 273 0.0038417798 0.427148952 0.003956170
#> 274 0.0033625281 0.005118926 0.001101108
#> 275 0.9666060199 0.999974103 0.961336529
#> 276 0.0004327544 0.005122497 0.001098261
#> 277 0.0469018642 0.028469353 0.004146162
#> 278 0.0044979844 0.381595933 0.544616145
#> 279 0.0006759861 0.607385444 0.934024448
#> 280 0.0048853649 0.077946255 0.001112814
#> 281 0.8376980961 0.949045878 0.039529861
#> 282 0.0004327347 0.005144710 0.001097383
#> 283 0.9993953295 0.999912139 0.935815304
#> 284 0.0048319481 0.123347859 0.001121454
#> 285 0.0541298261 0.005128926 0.074001250
#> 286 0.9980604208 0.936637615 0.999007041
#> 287 0.0082062521 0.029380484 0.008961581
#> 288 0.0088434263 0.016006147 0.013733498
#> 289 0.9976227870 0.999953133 0.989197995
#> 290 0.9778520454 0.999953659 0.998262902
#> 291 0.0144873023 0.005129086 0.003334373
#> 292 0.0067158056 0.998769317 0.016182872
#> 293 0.2386497964 0.458611199 0.257750910
#> 294 0.9956867369 0.999954432 0.999897859
#> 295 0.0038469766 0.005152803 0.018407454
#> 296 0.0064941312 0.962816762 0.015466785
#> 297 0.5907783690 0.745907136 0.052793111
#> 298 0.0033541528 0.015401558 0.001101818
#> 299 0.9747280698 0.999627780 0.999033237
#> 300 0.0033623759 0.005141124 0.001100228
#> 301 0.9999845319 0.999549056 0.979054775
#> 302 0.0037892787 0.005140602 0.001100642
#> 303 0.0003359557 0.989238158 0.016518184
#> 304 0.0003817321 0.498220467 0.001172326
#> 305 0.0120539598 0.745538989 0.995035629
#> 306 0.9998240295 0.946077156 0.756641873
#> 307 0.8614137847 0.049567438 0.998172714
#> 308 0.0004327347 0.005144710 0.001097383
#> 309 0.0004327347 0.005144710 0.001097383
#> 310 0.7285476350 0.996841091 0.498275854
#> 311 0.9932133594 0.999966419 0.992035195
#> 312 0.0004329822 0.004864971 0.001108440
#> 313 0.0004303498 0.028788321 0.001104094
#> 314 0.0048853649 0.077946255 0.001112814
#> 315 0.0055063783 0.748014843 0.082114315
#> 316 0.0049715865 0.005139155 0.001101790
#> 317 0.0005052127 0.005255504 0.190205181
#> 318 0.0011441856 0.076890905 0.010785540
#> 319 0.0007999154 0.041670993 0.977565076
#> 320 0.0004339940 0.027428861 0.010485774
#> 321 0.0015138725 0.005142416 0.001098472
#> 322 0.2807104431 0.073519635 0.051729513
#> 323 0.0038548452 0.005154467 0.020767688
#> 324 0.5010085709 0.013594195 0.003029840
#> 325 0.0004343470 0.004995002 0.004957152
#> 326 0.9998208196 0.985317688 0.019089857
#> 327 0.0042696555 0.005141882 0.003742391
#> 328 0.0006244319 0.999817665 0.998141782
#> 329 0.8866546932 0.969105535 0.870169606
#> 330 0.0027970187 0.015233532 0.001102572
#> 331 0.2264427950 0.526321536 0.016336082
#> 332 0.9998812596 0.999997676 0.998744899
#> 333 0.0004347963 0.057349413 0.020853754
#> 334 0.0004660053 0.005035821 0.087498773
#> 335 0.0050180642 0.596488779 0.191093048
#> 336 0.0004393464 0.005156957 0.018353890
#> 337 0.0004118765 0.207108670 0.001130062
#> 338 0.4831023648 0.939103371 0.169001817
#> 339 0.0011459567 0.077189943 0.010779633
#> 340 0.9993587657 0.878331770 0.999869962
#> 341 0.1265252264 0.424960633 0.089556937
#> 342 0.0105402672 0.999633242 0.284748805
#> 343 0.0127995624 0.497456147 0.003562547
#> 344 0.6063213478 0.969004636 0.352370992
#> 345 0.0004169819 0.157733041 0.001122378
#> 346 0.0004302944 0.028770488 0.001101155
#> 347 0.0049876456 0.005129887 0.004754226
#> 348 0.9322914709 0.990124327 0.002565175
#> 349 0.8656870292 0.999568914 0.444984450
#> 350 0.9996189840 0.998051733 0.782003929
#> 351 0.0038005373 0.027295723 0.010523478
#> 352 0.9970086286 0.998640391 0.983969837
#> 353 0.0034122698 0.015742867 0.020813463
#> 354 0.9998593893 0.995427029 0.998032068
#> 355 0.9943988966 0.999869705 0.038959866
#> 356 0.0059209461 0.015639429 0.001105259
#> 357 0.9436768610 0.955030482 0.584989910
#> 358 0.0039106649 0.027831384 0.043996546
#> 359 0.9999826293 0.998720594 0.998027017
#> 360 0.0004327537 0.005123248 0.001098231
#> 361 0.4250569966 0.992530022 0.146113399
#> 362 0.0042698883 0.005118521 0.003745534
#> 363 0.0004273929 0.056956528 0.001106153
#> 364 0.1266048699 0.014974919 0.011947740
#> 365 0.9998491622 0.999466082 0.985735113
#> 366 0.0004327347 0.005144710 0.001097383
#> 367 0.0033043471 0.077661813 0.001112064
#> 368 0.0029838077 0.943842828 0.016202536
#> 369 0.3655917300 0.960156356 0.020869328
#> 370 0.3927626760 0.031250486 0.980361008
#> 371 0.0375053286 0.896470361 0.004543138
#> 372 0.9984244177 0.999997230 0.708238944
#> 373 0.0132172917 0.028685436 0.001113773
#> 374 0.0037678018 0.059119752 0.006793458
#> 375 0.0004375496 0.005131299 0.013613085
#> 376 0.8310697902 0.999900249 0.065054618
#> 377 0.7084642228 0.999863229 0.987168784
#> 378 0.0004327347 0.005144710 0.001097383
#> 379 0.0004327347 0.005144710 0.001097383
#> 380 0.1184744610 0.488203528 0.001300465
#> 381 0.0073083105 0.046979216 0.001112214
#> 382 0.0149422174 0.997675398 0.970657930
#> 383 0.0042696555 0.005141882 0.003742391
#> 384 0.9986257947 0.999660284 0.998743641
#> 385 0.9880721305 0.999731534 0.999899247
#> 386 0.0478193674 0.120210685 0.003366644
#> 387 0.0017065824 0.029512076 0.152920389
#> 388 0.0143866043 0.005155393 0.040301921
#> 389 0.9364504968 0.003989537 0.016444268
#> 390 0.7678324911 0.998781563 0.964081197
#> 391 0.0004270200 0.075746115 0.005009998
#> 392 0.9970772761 0.999943650 0.997698935
#> 393 0.0218041499 0.004702514 0.001136214
#> 394 0.9996288723 0.988291079 0.989125638
#> 395 0.0049718229 0.005115813 0.001102718
#> 396 0.0034052843 0.015437837 0.018426781
#> 397 0.9342297109 0.951983644 0.002269483
#> 398 0.0004329647 0.004884688 0.001107660
#> 399 0.6205231428 0.014781771 0.009486935
#> 400 0.1447447281 0.014891447 0.003256374
#> 401 0.5934931337 0.984263382 0.998836334
#> 402 0.0004347963 0.057349413 0.020853754
#> 403 0.0037800156 0.015400009 0.001102232
#> 404 0.0047071042 0.004907937 0.045432451
#> 405 0.0004327347 0.005144710 0.001097383
#> 406 0.0662634956 0.906975654 0.084220598
#> 407 0.9999623042 0.998694145 0.973448717
#> 408 0.0123210795 0.997007486 0.985423965
#> 409 0.0489621839 0.005085220 0.003312715
#> 410 0.0042698768 0.005119673 0.003745379
#> 411 0.5159035835 0.779290860 0.338241381
#> 412 0.9764489546 0.999996106 0.280198004
#> 413 0.9997542653 0.999997614 0.958748708
#> 414 0.0027926544 0.933578886 0.984870646
#> 415 0.9998628908 0.997539125 0.978270055
#> 416 0.0033541528 0.015401558 0.001101818
#> 417 0.0006023343 0.725662493 0.775315539
#> 418 0.0004303498 0.028788321 0.001104094
#> 419 0.0004327347 0.005144710 0.001097383
#> 420 0.0004327544 0.005122497 0.001098261
#> 421 0.9996689147 0.978553306 0.998427287
#> 422 0.9998212828 0.999979120 0.968242919
#> 423 0.0042592583 0.015403818 0.003747708
#> 424 0.9386243465 0.022786675 0.138469287
#> 425 0.0003345340 0.996356418 0.016039338
#> 426 0.0004329750 0.004873095 0.001108118
#> 427 0.0004327347 0.005144710 0.001097383
#> 428 0.9366921219 0.999443538 0.021429239
#> 429 0.0004290927 0.055622921 0.004982000
#> 430 0.2228768357 0.655463861 0.017084318
#> 431 0.9795649037 0.999940059 0.999360535
#> 432 0.0004287530 0.057105138 0.004768322
#> 433 0.1143842538 0.005006691 0.003271034
#> 434 0.0034137912 0.005131033 0.018415111
#> 435 0.0031232391 0.347681456 0.014280474
#> 436 0.9999831514 0.999997258 0.998036615
#> 437 0.9979622805 0.999846697 0.978880334
#> 438 0.0003347501 0.957742968 0.001283720
#> 439 0.0081239378 0.761338322 0.632609786
#> 440 0.0011725718 0.979473004 0.015950745
#> 441 0.1131201062 0.055746454 0.003294893
#> 442 0.1493593439 0.955787435 0.994854129
#> 443 0.9998256012 0.999997708 0.998746918
#> 444 0.0014998142 0.043583331 0.001104309
#> 445 0.6719656256 0.998998015 0.293540095
#> 446 0.0144522304 0.015365877 0.003339222
#> 447 0.0004251962 0.078024342 0.001108460
#> 448 0.9914113788 0.044542513 0.069002172
#> 449 0.0037804742 0.078138075 0.018588817
#> 450 0.0024265366 0.072511261 0.001124457
#> 451 0.1452541833 0.005612306 0.986655648
#> 452 0.0003891872 0.426256250 0.001162002
#> 453 0.0004118512 0.207073790 0.001128273
#> 454 0.1016325133 0.055896623 0.003302279
#> 455 0.0004287568 0.043602023 0.001103228
#> 456 0.7760776931 0.811240888 0.027620049
#> 457 0.0004112874 0.248623413 0.011752786
#> 458 0.9998665977 0.999979386 0.974961645
#> 459 0.0606711257 0.167769668 0.826279656
#> 460 0.1943372027 0.743571925 0.006029341
#> 461 0.0004377785 0.028846510 0.020777174
#> 462 0.0015831537 0.152498734 0.001121040
#> 463 0.5529981197 0.224098262 0.031108580
#> 464 0.0759453689 0.947682347 0.939760144
#> 465 0.0144066622 0.028685187 0.003345839
#> 466 0.0003462250 0.897691106 0.020578316
#> 467 0.9249957407 0.998665791 0.389915579
#> 468 0.0071483013 0.989134172 0.099942426
#> 469 0.0038196990 0.043681513 0.020875407
#> 470 0.0368526080 0.077060519 0.001144878
#> 471 0.0449475157 0.138848396 0.003374664
#> 472 0.0003318553 0.980446526 0.001245896
#> 473 0.9996201926 0.998710595 0.999875071
#> 474 0.9832536060 0.949487015 0.003084913
#> 475 0.0038033495 0.004990999 0.004971833
#> 476 0.0004340275 0.027306955 0.010493629
#> 477 0.0049715865 0.005139155 0.001101790
#> 478 0.0104288977 0.997932590 0.340525164
#> 479 0.9999847386 0.999961934 0.999152675
#> 480 0.9945292456 0.999967321 0.998304972
#> 481 0.0037982641 0.443368997 0.140185519
#> 482 0.9165992599 0.904521754 0.149190632
#> 483 0.6339573609 0.993575390 0.041657466
#> 484 0.0813807132 0.999930456 0.994595007
#> 485 0.1071492880 0.576385945 0.014869003
#> 486 0.0004402481 0.005158627 0.020707401
#> 487 0.0004225364 0.139082664 0.011127251
#> 488 0.1792279297 0.956952453 0.996073181
#> 489 0.9858411596 0.999907961 0.978411917
#> 490 0.0453062318 0.032548737 0.381583548
#> 491 0.0049340909 0.005186146 0.067427656
#> 492 0.0049099996 0.057144255 0.001109664
#> 493 0.6266145540 0.882802875 0.035687897
#> 494 0.9899096794 0.991463088 0.999035070
#> 495 0.0007778123 0.015147143 0.020741610
#> 496 0.0031573141 0.744557585 0.014627982
#> 497 0.0037238954 0.077665059 0.001112447
#> 498 0.0004341389 0.005135443 0.004735277
#> 499 0.0004393464 0.005156957 0.018353890
#> 500 0.9827344250 0.999228254 0.002573633
#> 501 0.0004745134 0.028873269 0.117478614
#> 502 0.9216800042 0.324397747 0.249432256
#> 503 0.8298580941 0.003978400 0.002836752
#> 504 0.0141999538 0.043806120 0.060801778
#> 505 0.9986217687 0.999549759 0.976400652
#> 506 0.8277290738 0.999987986 0.959721272
#> 507 0.0004644705 0.005190007 0.083893941
#> 508 0.0087478461 0.016032312 0.001107263
#> 509 0.9949125975 0.993817062 0.078209109
#> 510 0.0067158619 0.998769356 0.016184996
#> 511 0.0004327347 0.005144710 0.001097383
#> 512 0.0042310799 0.043388602 0.003764841
#> 513 0.0049715865 0.005139155 0.001101790
#> 514 0.0004273894 0.056976605 0.001106083
#> 515 0.0004163689 0.199122190 0.011469241
#> 516 0.0042773100 0.122523054 0.016318131
#> 517 0.0015132294 0.015421338 0.001100088
#> 518 0.9991281403 0.684909040 0.998946700
#> 519 0.5920059379 0.999898789 0.002149547
#> 520 0.0524708747 0.994743560 0.080774140
#> 521 0.0042696555 0.005141882 0.003742391
#> 522 0.0003927312 0.429419139 0.012790693
#> 523 0.2198090054 0.350537209 0.312005107
#> 524 0.7560368077 0.999928841 0.818936934
#> 525 0.0004353682 0.043510564 0.018464326
#> 526 0.5119515022 0.074271021 0.003046478
#> 527 0.9991692238 0.189581028 0.950925105
#> 528 0.0004316668 0.015700698 0.001100230
#> 529 0.0004317259 0.078196435 0.018535923
#> 530 0.0004327347 0.005144710 0.001097383
#> 531 0.1155470185 0.990313826 0.802717621
#> 532 0.0003348674 0.993127210 0.016022302
#> 533 0.0004368803 0.028837387 0.018415882
#> 534 0.0004339940 0.027428861 0.010485774
#> 535 0.0296868086 0.027673867 0.044913124
#> 536 0.0016688876 0.005175185 0.075134796
#> 537 0.9390624637 0.099309165 0.223485419
#> 538 0.9941589677 0.999838998 0.243839236
#> 539 0.0063678688 0.941384685 0.015804171
#> 540 0.9659285502 0.996036547 0.014666398
#> 541 0.9999088553 0.988091558 0.996736131
#> 542 0.3494164480 0.004639611 0.013227557
#> 543 0.9494940439 0.999996119 0.987956304
#> 544 0.0067586418 0.998745463 0.017810542
#> 545 0.9810503205 0.998526553 0.014463118
#> 546 0.9969155432 0.467715561 0.168782454
#> 547 0.0004251962 0.078024342 0.001108460
#> 548 0.9683965937 0.965752673 0.981298284
#> 549 0.0049436773 0.028740158 0.001105545
#> 550 0.9880900260 0.999997401 0.998288352
#> 551 0.0143496433 0.005165049 0.053870772
#> 552 0.0143321025 0.005147279 0.060543438
#> 553 0.0478671834 0.057003442 0.060537935
#> 554 0.9996450816 0.999081018 0.708269107
#> 555 0.9999834858 0.999514947 0.846589210
#> 556 0.0004341389 0.005135443 0.004735277
#> 557 0.0491304194 0.988047214 0.005698863
#> 558 0.0049743345 0.004867823 0.001112572
#> 559 0.0038166474 0.980425696 0.001249732
#> 560 0.8006160490 0.374937713 0.016467964
#> 561 0.9920831771 0.965810098 0.016321922
#> 562 0.0074732598 0.817806761 0.983894835
#> 563 0.0021300908 0.004907146 0.005104033
#> 564 0.6139061617 0.992459913 0.427316053
#> 565 0.0004287568 0.043602023 0.001103228
#> 566 0.0122928946 0.005096130 0.001110370
#> 567 0.1022620424 0.028094202 0.003289763
#> 568 0.3385043092 0.026543958 0.013162186
#> 569 0.0015132294 0.015421338 0.001100088
#> 570 0.9970314910 0.998652307 0.999043682
#> 571 0.0144873023 0.005129086 0.003334373
#> 572 0.0004762305 0.148410555 0.160726998
#> 573 0.9991335506 0.994234288 0.995783692
#> 574 0.0004639563 0.003807962 0.079147675
#> 575 0.0005307887 0.029791295 0.265307103
#> 576 0.0015138725 0.005142416 0.001098472
#> 577 0.9876294875 0.909180758 0.997105096
#> 578 0.2005940353 0.998776712 0.074560243
#> 579 0.9856708591 0.995609564 0.003092255
#> 580 0.7009349505 0.241685943 0.999636985
#> 581 0.9723020085 0.986045695 0.996267453
#> 582 0.0107271061 0.990307499 0.932600270
#> 583 0.0033748669 0.004991508 0.004969965
#> 584 0.0036724336 0.495306527 0.013210616
#> 585 0.9998256476 0.999962520 0.999900055
#> 586 0.0028014709 0.015230430 0.001102621
#> 587 0.9986242913 0.999547938 0.998743555
#> 588 0.9999829274 0.999997211 0.978631951
#> 589 0.0209624170 0.304120524 0.001167562
#> 590 0.1249430938 0.075947340 0.012036476
#> 591 0.2778286433 0.014411963 0.006253166
#> 592 0.9998698191 0.999968209 0.999897962
#> 593 0.9999787585 0.999996649 0.222866110
#> 594 0.9828140615 0.999967787 0.003488667
#> 595 0.9973832592 0.991376486 0.786886696
#> 596 0.9858272267 0.964588216 0.276029279
#> 597 0.0044034584 0.497495405 0.005066022
#> 598 0.0047009583 0.005148892 0.045062480
#> 599 0.0158503953 0.126689741 0.070046444
#> 600 0.0034207822 0.005132684 0.020776306
#> 601 0.8590645082 0.023308049 0.135086322
#> 602 0.9999608735 0.999143931 0.778082185
#> 603 0.0024901575 0.040322887 0.001120375
#> 604 0.0133097652 0.426478686 0.004046858
#> 605 0.0131460642 0.005128018 0.001109783
#> 606 0.0004304670 0.042380901 0.004975501
#> 607 0.0004363650 0.035474013 0.014682033
#> 608 0.9970535353 0.999997218 0.978677135
#> 609 0.0003994986 0.326494652 0.001146436
#> 610 0.0049715865 0.005139155 0.001101790
#> 611 0.0004339940 0.027428861 0.010485774
#> 612 0.0164857417 0.691829560 0.001219519
#> 613 0.0032773076 0.436604273 0.001169255
#> 614 0.0037392273 0.075792200 0.005013598
#> 615 0.0005064472 0.630681826 0.432693304
#> 616 0.9291413228 0.999083341 0.002563630
#> 617 0.0037892787 0.005140602 0.001100642
#> 618 0.0004393464 0.005156957 0.018353890
#> 619 0.9200279674 0.004043178 0.044980522
#> 620 0.0121944512 0.108704653 0.735212472
#> 621 0.0033043343 0.077672379 0.001112037
#> 622 0.3756464310 0.491736002 0.413825072
#> 623 0.5163541484 0.274703545 0.125612699
#> 624 0.0064887514 0.975175622 0.001256079
#> 625 0.1849221433 0.094666230 0.001298760
#> 626 0.0015487387 0.028839845 0.020799184
#> 627 0.0003995376 0.326634959 0.001149544
#> 628 0.0463734024 0.077248661 0.004167827
#> 629 0.0004391736 0.015453547 0.020736913
#> 630 0.0009385079 0.044363867 0.001103922
#> 631 0.0047004052 0.005170578 0.045029182
#> 632 0.0144873023 0.005129086 0.003334373
#> 633 0.3238127071 0.004794082 0.075631364
#> 634 0.9998235410 0.999664588 0.998298645
#> 635 0.9947756039 0.999392845 0.999838395
#> 636 0.0005581811 0.990101888 0.776858181
#> 637 0.0007640737 0.015104901 0.001099232
#> 638 0.9999847662 0.999997679 0.999899895
#> 639 0.7812333361 0.996856434 0.140775113
#> 640 0.6978913613 0.950133019 0.003279490
#> 641 0.0004339940 0.027428861 0.010485774
#> 642 0.9158514871 0.994899149 0.786925113
#> 643 0.0004327347 0.005144710 0.001097383
#> 644 0.0045694988 0.027761422 0.034963998
#> 645 0.0049718229 0.005115813 0.001102718
#> 646 0.0041519905 0.121206050 0.003801436
#> 647 0.0785895572 0.980162138 0.020055754
#> 648 0.9965676168 0.996069541 0.988442938
#> 649 0.9995813147 0.998538276 0.811806427
#> 650 0.0143106414 0.056812471 0.003360819
#> 651 0.9935051090 0.837227822 0.998316846
#> 652 0.0004382734 0.015448584 0.018380111
#> 653 0.0004327347 0.005144710 0.001097383
#> 654 0.0179715303 0.160487260 0.001139569
#> 655 0.0106853802 0.123311526 0.001126121
#> 656 0.8726438951 0.998488486 0.039889310
#> 657 0.0004335165 0.043674323 0.013673879
#> 658 0.0378286714 0.028603699 0.019050416
#> 659 0.0178334923 0.057071358 0.069705108
#> 660 0.0125387954 0.346818061 0.319564316
#> 661 0.0004350670 0.028818967 0.013648505
#> 662 0.0004327347 0.005144710 0.001097383
#> 663 0.0004327347 0.005144710 0.001097383
#> 664 0.3673427713 0.974966035 0.001650120
#> 665 0.0037892787 0.005140602 0.001100642
#> 666 0.9918277003 0.004006937 0.176167372
#> 667 0.5592582317 0.485474473 0.009563835
#> 668 0.0003890696 0.427284192 0.001161545
#> 669 0.0029395189 0.946277168 0.001247600
#> 670 0.0004327347 0.005144710 0.001097383
#> 671 0.0004316733 0.015412189 0.001098978
#> 672 0.0793153606 0.809306879 0.914599545
#> 673 0.9539395123 0.999429088 0.152684347
#> 674 0.0004375508 0.005130142 0.013613643
#> 675 0.0004327554 0.005121344 0.001098307
#> 676 0.0143315913 0.005169765 0.060497920
#> 677 0.9968339908 0.999215135 0.997941627
#> 678 0.1548844201 0.032938798 0.001254480
#> 679 0.0126975839 0.015868864 0.013793390
#> 680 0.0004339028 0.057331819 0.018483923
#> 681 0.8316407502 0.556674750 0.012257369
#> 682 0.9984917004 0.999997200 0.998035966
#> 683 0.0004587574 0.029069441 0.075840965
#> 684 0.9969989711 0.989232854 0.998704046
#> 685 0.0033574477 0.057258218 0.013733684
#> 686 0.6448341541 0.089753843 0.009754314
#> 687 0.4762999705 0.587195898 0.031723557
#> 688 0.0141016926 0.078005382 0.054422605
#> 689 0.5011067262 0.004528567 0.012972442
#> 690 0.0004316733 0.015412189 0.001098978
#> 691 0.0003502275 0.843510437 0.015165058
#> 692 0.0058859516 0.005262964 0.210549742
#> 693 0.8868612046 0.509061431 0.994889868
#> 694 0.0458326879 0.005254939 0.271122110
#> 695 0.9870904144 0.032273180 0.998511717
#> 696 0.0004348461 0.057101961 0.020869618
#> 697 0.0025020628 0.004754636 0.001114887
#> 698 0.0033864327 0.519078471 0.022250442
#> 699 0.9967541971 0.463034336 0.017818710
#> 700 0.8288983822 0.021438924 0.026637931
#> 701 0.1553077300 0.994165565 0.999458489
#> 702 0.0004375259 0.005153585 0.013602339
#> 703 0.9960265661 0.544471252 0.994806159
#> 704 0.0042169008 0.057172996 0.003768749
#> 705 0.9364560030 0.998321162 0.702494657
#> 706 0.0037437433 0.899398854 0.050906445
#> 707 0.0033623759 0.005141124 0.001100228
#> 708 0.0005126778 0.005292786 0.209750814
#> 709 0.9996205297 0.999997644 0.976384188
#> 710 0.0015983657 0.027251790 0.010507381
#> 711 0.9627142281 0.999590885 0.981609737
#> 712 0.0003830843 0.497767414 0.005048513
#> 713 0.9105244949 0.999892148 0.622066071
#> 714 0.0004375259 0.005153585 0.013602339
#> 715 0.9989565685 0.999961577 0.998744085
#> 716 0.0067935995 0.999418012 0.023105761
#> 717 0.9792237402 0.999264419 0.776353251
#> 718 0.0223368415 0.224826803 0.014308996
#> 719 0.0004327347 0.005144710 0.001097383
#> 720 0.0007338873 0.356187862 0.959288105
#> 721 0.0066571709 0.989247150 0.016085962
#> 722 0.9941239165 0.999576102 0.267892871
#> 723 0.1188552536 0.016018857 0.777910466
#> 724 0.0007640737 0.015104901 0.001099232
#> 725 0.0004320986 0.057296296 0.013699178
#> 726 0.0006227163 0.058204317 0.517188365
#> 727 0.0007664296 0.015078296 0.004743039
#> 728 0.9999847070 0.999665039 0.998744647
#> 729 0.0004327544 0.005122497 0.001098261
#> 730 0.0005051419 0.005278827 0.190081894
#> 731 0.0004327347 0.005144710 0.001097383
#> 732 0.0113338003 0.899007098 0.045715321
#> 733 0.0142834919 0.029073720 0.055461248
#> 734 0.0004335165 0.043674323 0.013673879
#> 735 0.0004118512 0.207073790 0.001128273
#> 736 0.0374790605 0.005077345 0.001134261
#> 737 0.0004302944 0.028770488 0.001101155
#> 738 0.0006254717 0.005479633 0.504070513
#> 739 0.0427546180 0.005084968 0.021471309
#> 740 0.9999845143 0.999961326 0.968246942
#> 741 0.6532100515 0.534472503 0.010527765
#> 742 0.3940453605 0.976070290 0.119864124
#> 743 0.9968088635 0.999997595 0.992170359
#> 744 0.0034052843 0.015437837 0.018426781
#> 745 0.9562819728 0.004493729 0.985662224
#> 746 0.9997602014 0.991298364 0.999868040
#> 747 0.7037049637 0.999907606 0.044604292
#> 748 0.0483161139 0.958186797 0.016995894
#> 749 0.0017285770 0.029756690 0.169548968
#> 750 0.0004343541 0.004990252 0.004964656
#> 751 0.1220335771 0.004948288 0.004836557
#> 752 0.0033623759 0.005141124 0.001100228
#> 753 0.9970768024 0.999925008 0.997698873
#> 754 0.0287897300 0.005087935 0.001125817
#> 755 0.0037728679 0.028928259 0.001134218
#> 756 0.0018659522 0.199929525 0.001129337
#> 757 0.9893274297 0.127953902 0.251200797
#> 758 0.9998477366 0.999956344 0.708718195
#> 759 0.0144946804 0.004869759 0.003365527
#> 760 0.0004302944 0.028770488 0.001101155
#> 761 0.0004197648 0.328270063 0.059290890
#> 762 0.0037239098 0.077654494 0.001112474
#> 763 0.0003615571 0.750792103 0.020217170
#> 764 0.9960029356 0.872727436 0.901552556
#> 765 0.1419065716 0.982699135 0.013269875
#> 766 0.0004327347 0.005144710 0.001097383
#> 767 0.9984703465 0.999972802 0.999899987
#> 768 0.0049715865 0.005139155 0.001101790
#> 769 0.0168994433 0.077719162 0.001124596
#> 770 0.0004327347 0.005144710 0.001097383
#> 771 0.0038072704 0.057305593 0.020913498
#> 772 0.0045138898 0.429155114 0.012833490
#> 773 0.0089373814 0.996605582 0.134086592
#> 774 0.0051886582 0.401936119 0.749729491
#> 775 0.9966137539 0.998145012 0.983905368
#> 776 0.1450494522 0.004969120 0.003251591
#> 777 0.9984849757 0.999710601 0.998717940
#> 778 0.0004551125 0.005008912 0.059066813
#> 779 0.0049715865 0.005139155 0.001101790
#> 780 0.9826190123 0.959286060 0.451102752
#> 781 0.0015181985 0.027416950 0.010495924
#> 782 0.9984551089 0.999979180 0.999152029
#> 783 0.0004303498 0.028788321 0.001104094
#> 784 0.0004402481 0.005158627 0.020707401
#> 785 0.9999847464 0.999961979 0.998076686
#> 786 0.0320482848 0.043299937 0.004017284
#> 787 0.0363083607 0.005081497 0.004038642
#> 788 0.0004022745 0.904995384 0.211090732
#> 789 0.9969838978 0.023171206 0.140622415
#> 790 0.9956614993 0.999979930 0.996440363
#> 791 0.0037668839 0.508193473 0.019671149
#> 792 0.0042696555 0.005141882 0.003742391
#> 793 0.9977120058 0.004041311 0.247287601
#> 794 0.0004251962 0.078024342 0.001108460
#> 795 0.9489530909 0.999937329 0.222928383
#> 796 0.1469653663 0.861162999 0.995851503
#> 797 0.0049260906 0.043556759 0.001107607
#> 798 0.0004326742 0.077889837 0.020927675
#> 799 0.0004327544 0.005122497 0.001098261
#> 800 0.0091702374 0.944759284 0.999011771
#> 801 0.0003370790 0.993624198 0.023562265
#> 802 0.0003383832 0.958859754 0.015824486
#> 803 0.0136113062 0.263720659 0.031417321
#> 804 0.0003905895 0.414000186 0.001167457
#> 805 0.1739061997 0.989371439 0.023920261
#> 806 0.0037799590 0.015688298 0.001103487
#> 807 0.9672087026 0.999425707 0.998270773
#> 808 0.0004393464 0.005156957 0.018353890
#> 809 0.0004252433 0.077722607 0.001109225
#> 810 0.1325959455 0.005338538 0.516587813
#> 811 0.0066894600 0.987469228 0.023595838
#> 812 0.3204543071 0.039742736 0.003165451
#> 813 0.0050471958 0.005151340 0.018426320
#> 814 0.0004351323 0.028836112 0.013682721
#> 815 0.0034135957 0.005153331 0.018400642
#> 816 0.0004329822 0.004864971 0.001108440
#> 817 0.0004539188 0.005171025 0.056356158
#> 818 0.9745517459 0.999427502 0.987956835
#> 819 0.0005683546 0.032536926 0.365476657
#> 820 0.0041957998 0.077984594 0.003779291
#> 821 0.0004287568 0.043602023 0.001103228
#> 822 0.0037961009 0.043640588 0.013713506
#> 823 0.0004327347 0.005144710 0.001097383
#> 824 0.9992545789 0.999696713 0.826287232
#> 825 0.0004327554 0.005121344 0.001098307
#> 826 0.0274576774 0.202823891 0.001154378
#> 827 0.9813707788 0.999997236 0.989442995
#> 828 0.0003972200 0.348488287 0.001149568
#> 829 0.0016978752 0.258035629 0.001141943
#> 830 0.9996319135 0.999940678 0.999878008
#> 831 0.9998799870 0.999979264 0.979058848
#> 832 0.9968188361 0.986726498 0.702185383
#> 833 0.0004327537 0.005123248 0.001098231
#> 834 0.9965957958 0.999476964 0.949737531
#> 835 0.0021958834 0.298903448 0.012181974
#> 836 0.0049876456 0.005129887 0.004754226
#> 837 0.9998801662 0.999759027 0.968292241
#> 838 0.9998531985 0.999955645 0.999897960
#> 839 0.9994147295 0.999925806 0.844567712
#> 840 0.0004291339 0.201648132 0.047795201
#> 841 0.0122438100 0.045212451 0.786911102
#> 842 0.9986217013 0.999997643 0.968277117
#> 843 0.0049594476 0.015395719 0.001103378
#> 844 0.1095383065 0.199525181 0.003362803
#> 845 0.9998639652 0.999997633 0.968243923
#> 846 0.1476634506 0.014924337 0.005063114
#> 847 0.9973702048 0.999896103 0.998718456
#> 848 0.0004341389 0.005135443 0.004735277
#> 849 0.0042457542 0.028755056 0.003754969
#> 850 0.9996209128 0.999961504 0.979060754
#> 851 0.0144873023 0.005129086 0.003334373
#> 852 0.0032783555 0.155296014 0.013916348
#> 853 0.9999845328 0.999592490 0.976380778
#> 854 0.0033623759 0.005141124 0.001100228
#> 855 0.0004327347 0.005144710 0.001097383
#> 856 0.0288950872 0.025839593 0.010837102
#> 857 0.0363066011 0.005102798 0.004035515
#> 858 0.0356984442 0.077434922 0.004069490
#> 859 0.0608252533 0.976401008 0.004849471
#> 860 0.0004316733 0.015412189 0.001098978
#> 861 0.0556848524 0.999441606 0.001447692
#> 862 0.0116412426 0.896965909 0.999516628
#> 863 0.1416429012 0.991474584 0.965771117
#> 864 0.1090524501 0.196530691 0.033469824
#> 865 0.0049876456 0.005129887 0.004754226
#> 866 0.0323367553 0.005086323 0.004002275
#> 867 0.0003453385 0.850551795 0.001229492
#> 868 0.0036724336 0.495306527 0.013210616
#> 869 0.9992685070 0.966409483 0.018984546
#> 870 0.0004327347 0.005144710 0.001097383
#> 871 0.0032726643 0.995017912 0.004389703
#> 872 0.0004393464 0.005156957 0.018353890
#> 873 0.0067024586 0.996505370 0.016182293
#> 874 0.0133716850 0.005141732 0.020936745
#> 875 0.0047331783 0.206995125 0.001135443
#> 876 0.9963549181 0.988169191 0.999034075
#> 877 0.9998109876 0.991963068 0.998290267
#> 878 0.0004245786 0.084091567 0.001110012
#> 879 0.0050471958 0.005151340 0.018426320
#> 880 0.7951122711 0.985789966 0.645656713
#> 881 0.0004339940 0.027428861 0.010485774
#> 882 0.0035722998 0.692976506 0.004091790
#> 883 0.6568997568 0.999321761 0.999782654
#> 884 0.0041501916 0.123298459 0.003807948
#> 885 0.9995622549 0.982572319 0.988381095
#> 886 0.0119842861 0.040223555 0.886319360
#> 887 0.0003973349 0.347501435 0.001150100
#> 888 0.8583010979 0.758777804 0.728504045
#> 889 0.0033642930 0.004861574 0.001111315
#> 890 0.0004327347 0.005144710 0.001097383
#> 891 0.0004762305 0.148410555 0.160726998
#> 892 0.0004341389 0.005135443 0.004735277
#> 893 0.5450609932 0.004469636 0.001627000
#> 894 0.0004369540 0.028855479 0.018464176
#> 895 0.0004207247 0.121264832 0.001115106
#> 896 0.0004327347 0.005144710 0.001097383
#> 897 0.0075507642 0.989849850 0.170274881
#> 898 0.6792114002 0.999862473 0.197616815
#> 899 0.0007778123 0.015147143 0.020741610
#> 900 0.9970831528 0.999997622 0.998743354
#> 901 0.9739031096 0.995039593 0.999026578
#> 902 0.0116430175 0.849768395 0.004084435
#> 903 0.0144950094 0.004858198 0.003366915
#> 904 0.0015138725 0.005142416 0.001098472
#> 905 0.0287884598 0.005110004 0.001124915
#> 906 0.0004327544 0.005122497 0.001098261
#> 907 0.0361098627 0.028541636 0.004047190
#> 908 0.3093850546 0.004794307 0.050985001
#> 909 0.9998661374 0.999972738 0.999899887
#> 910 0.0004327347 0.005144710 0.001097383
#> 911 0.0037892787 0.005140602 0.001100642
#> 912 0.0004287568 0.043602023 0.001103228
#> 913 0.0037239098 0.077654494 0.001112474
#> 914 0.0004265985 0.077894075 0.004781540
#> 915 0.7178330165 0.993358162 0.134269275
#> 916 0.9578653934 0.455594292 0.020249223
#> 917 0.6036119485 0.004401401 0.009231504
#> 918 0.0003531781 0.815308550 0.015046135
#> 919 0.0004327347 0.005144710 0.001097383
#> 920 0.0007122702 0.393497934 0.921454765
#> 921 0.0004216462 0.158102016 0.013909521
#> 922 0.0004252449 0.077712035 0.001109252
#> 923 0.3943092128 0.962894580 0.768561650
#> 924 0.3281333747 0.793389897 0.984048300
#> 925 0.9998082945 0.999952662 0.998268625
#> 926 0.0004273500 0.057202795 0.001105295
#> 927 0.0038002683 0.027407611 0.010516239
#> 928 0.0334925634 0.610914502 0.023813901
#> 929 0.8594842624 0.894348622 0.482696837
#> 930 0.9981039125 0.999753674 0.958665978
#> 931 0.0004327347 0.005144710 0.001097383
#> 932 0.9984529101 0.999794020 0.998693668
#> 933 0.6907711381 0.976295309 0.140140254
#> 934 0.9667629293 0.999632537 0.967192427
#> 935 0.0168631672 0.900654223 0.015799542
#> 936 0.0033732545 0.005131857 0.004747508
#> 937 0.6430811278 0.034093470 0.883848563
#> 938 0.9999816330 0.990992461 0.999897376
#> 939 0.0066166481 0.975246021 0.023634865
#> 940 0.0048090356 0.740342234 0.201040885
#> 941 0.0032478130 0.431723782 0.001165548
#> 942 0.0485241322 0.224457140 0.001182110
#> 943 0.0144873023 0.005129086 0.003334373
#> 944 0.1186680042 0.055630929 0.001220721
#> 945 0.9526055955 0.998991939 0.039197683
#> 946 0.0015138725 0.005142416 0.001098472
#> 947 0.9595372914 0.997791658 0.841899479
#> 948 0.0004402481 0.005158627 0.020707401
#> 949 0.0074377199 0.031820001 0.312612171
#> 950 0.0007642261 0.014656150 0.004970836
#> 951 0.0016168690 0.124551946 0.001119356
#> 952 0.1450764109 0.887939685 0.975829643
#> 953 0.6264597048 0.004386165 0.014708744
#> 954 0.0004568616 0.043920520 0.075267056
#> 955 0.0011459567 0.077189943 0.010779633
#> 956 0.0015037859 0.078116621 0.013751028
#> 957 0.0004251962 0.078024342 0.001108460
#> 958 0.9999848238 0.999560661 0.998301483
#> 959 0.9999847525 0.999962002 0.998299087
#> 960 0.0004327347 0.005144710 0.001097383
#> 961 0.9984247232 0.999975604 0.708248727
#> 962 0.0048859029 0.077644787 0.001113582
#> 963 0.0031222715 0.348721546 0.014273611
#> 964 0.0005126778 0.005292786 0.209750814
#> 965 0.4757448931 0.004950783 0.673412048
#> 966 0.0003501577 0.844114011 0.015163782
#> 967 0.0034135957 0.005153331 0.018400642
#> 968 0.9962931847 0.982701908 0.810736583
#> 969 0.0489621839 0.005085220 0.003312715
#> 970 0.9870899066 0.987915765 0.038282510
#> 971 0.0004316733 0.015412189 0.001098978
#> 972 0.9965717798 0.888649852 0.998674400
#> 973 0.0037668839 0.508193473 0.019671149
#> 974 0.0038312971 0.005127175 0.013653008
#> 975 0.0004339940 0.027428861 0.010485774
#> 976 0.0004172187 0.155160763 0.001120270
#> 977 0.9996940276 0.999955174 0.999358660
#> 978 0.0345376072 0.027592923 0.037260476
#> 979 0.0029270736 0.587232711 0.013761498
#> 980 0.1025720045 0.016987174 0.028433014
#> 981 0.0004878402 0.029524625 0.152793782
#> 982 0.9997315137 0.999997537 0.868271083
#> 983 0.0004941279 0.029769351 0.169411347
#> 984 0.7200445096 0.993646558 0.002095834
#> 985 0.0004273500 0.057202795 0.001105295
#> 986 0.3766531646 0.058768893 0.001477341
#> 987 0.9955972965 0.999292237 0.019035538
#> 988 0.9982827259 0.999592649 0.998260883
#> 989 0.0004340259 0.027312970 0.010493241
#> 990 0.0004941999 0.029646088 0.169509173
#> 991 0.9477843837 0.004449092 0.845160067
#> 992 0.0033721315 0.027410314 0.010512365
#> 993 0.9704209377 0.985249903 0.867765897
#> 994 0.5224961248 0.035140109 0.860246671
#> 995 0.0007636981 0.015036983 0.001100143
#> 996 0.0003501577 0.844114011 0.015163782
#> 997 0.9300840681 0.004032508 0.067307630
#> 998 0.0004327554 0.005121344 0.001098307
#> 999 0.5265446824 0.280893479 0.087531899
#> 1000 0.0014163555 0.425603427 0.001163308