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Type 'q()' to quit R. > library("runjags") > set.seed(2022-03-09) > > N <- 600 > status <- rbinom(N, 1, rep(c(0.25,0.5,0.75), each=N/3)) > testdata <- data.frame(Population = rep(1:3, each=N/3), Test1 = rbinom(N, 1, status*0.75 + (1-status)*0.05), Test2 = rbinom(N, 1, status*0.75 + (1-status)*0.05), Test3=rbinom(N, 1, status*0.75 + (1-status)*0.05)) > > template_huiwalter(testdata, outfile="huiwalter_model.txt", covariance=TRUE, cov_as_cor=TRUE) The model and data have been written to huiwalter_model.txt in the current working directory *** NOTE: The template provided should be examined and modified (including checking *** *** priors, covariance terms, and verifying the code) before running the model! *** Warning messages: 1: In template_huiwalter(testdata, outfile = "huiwalter_model.txt", : Setting covariance=TRUE is now deprecated; please specify a data frame of desired covariance terms instead (see ?template_huiwalter) 2: In template_huiwalter(testdata, outfile = "huiwalter_model.txt", : You have specified a lot of active conditional depdendence terms, which is not recommended; if you really need this many conditional depdendence terms then you should probably use an alternative model formulation 3: In template_huiwalter(testdata, outfile = "huiwalter_model.txt", : The cov_as_cor option is now deprecated and ignored (i.e. always interpreted as FALSE) > results <- run.jags("huiwalter_model.txt") INFORMATION: Es konnten keine Dateien mit dem angegebenen Muster gefunden werden. Loading required namespace: rjags Compiling rjags model... Calling the simulation using the rjags method... Adapting the model for 1000 iterations... Burning in the model for 4000 iterations... Running the model for 10000 iterations... Simulation complete Calculating summary statistics... Calculating the Gelman-Rubin statistic for 45 variables.... Finished running the simulation > #unlink("huiwalter_model.txt") > results JAGS model summary statistics from 20000 samples (chains = 2; adapt+burnin = 5000): Lower95 Median Upper95 Mean SD se[1] 0.59414 0.68361 0.76974 0.68199 0.045117 se[2] 0.58957 0.68157 0.76988 0.68014 0.046536 se[3] 0.6169 0.70937 0.79657 0.70726 0.046655 sp[1] 0.88043 0.93079 0.97728 0.92981 0.024884 sp[2] 0.89934 0.94519 0.9862 0.94395 0.022556 sp[3] 0.89431 0.93962 0.98419 0.93874 0.023174 prev[1] 0.19423 0.27099 0.35362 0.27283 0.041211 prev[2] 0.33724 0.43532 0.54182 0.43833 0.052513 prev[3] 0.67709 0.78068 0.90906 0.78638 0.059799 covse_1_2 -0.0096367 0.015086 0.039977 0.015518 0.013012 covse_1_3 -0.014317 0.009541 0.036034 0.0099212 0.013235 covse_2_3 -0.016239 0.0089012 0.035558 0.0094891 0.013712 corse_1_2 -0.083313 0.076291 0.20685 0.0701 0.073791 corse_1_3 -0.17847 0.050348 0.19067 0.033473 0.096143 corse_2_3 -0.20532 0.046697 0.18897 0.028611 0.10167 covsp_1_2 -0.0018216 0.00072553 0.0040721 0.00085022 0.0014925 covsp_1_3 -0.0024154 0.00038174 0.0035847 0.00047264 0.0014753 covsp_2_3 -0.0014336 0.0011964 0.0047354 0.0014171 0.0015892 corsp_1_2 -0.34256 0.018326 0.13864 -0.020729 0.12189 corsp_1_3 -0.38469 0.0091803 0.10852 -0.051199 0.13603 corsp_2_3 -0.27849 0.032365 0.16707 0.013565 0.10254 check_outcome_RRR[1,1] -9 11 28 11.081 9.5026 check_outcome_RRR[2,1] -15 -5 1 -5.7198 4.3297 check_outcome_RRR[3,1] -13 -4 2 -4.4973 3.9252 check_outcome_RRR[4,1] -6 1 5 0.4958 2.9994 check_outcome_RRR[5,1] -11 -3 4 -3.4301 4.1831 check_outcome_RRR[6,1] -9 -3 2 -2.823 3.0979 check_outcome_RRR[7,1] 0 5 11 5.1251 3.0792 check_outcome_RRR[8,1] -10 0 9 -0.23125 5.1516 check_outcome_RRR[1,2] -21 -2 16 -1.7857 9.6256 check_outcome_RRR[2,2] -5 3 9 2.717 3.8431 check_outcome_RRR[3,2] -5 2 8 1.427 3.5691 check_outcome_RRR[4,2] -6 2 8 1.2993 3.7885 check_outcome_RRR[5,2] -10 -1 5 -0.9077 3.9211 check_outcome_RRR[6,2] -9 0 6 -0.2907 3.9429 check_outcome_RRR[7,2] -9 0 6 -0.2313 3.9069 check_outcome_RRR[8,2] -16 -2 8 -2.2279 6.2727 check_outcome_RRR[1,3] -17 0 15 -0.06215 8.3264 check_outcome_RRR[2,3] -12 -2 4 -2.3204 4.2018 check_outcome_RRR[3,3] -10 -1 5 -1.5891 4.0236 check_outcome_RRR[4,3] -10 2 10 1.4037 5.1401 check_outcome_RRR[5,3] -10 -1 7 -0.98055 4.5068 check_outcome_RRR[6,3] -4 7 16 6.3541 5.2819 check_outcome_RRR[7,3] -12 -1 8 -1.4373 5.2963 check_outcome_RRR[8,3] -18 -1 13 -1.3683 8.1097 Mode MCerr MC%ofSD SSeff AC.10 psrf se[1] 0.68459 0.0012774 2.8 1247 0.28034 1.0028 se[2] 0.6877 0.0013134 2.8 1255 0.30052 1.0042 se[3] 0.71157 0.0013162 2.8 1257 0.30886 1.0029 sp[1] 0.93191 0.00061261 2.5 1650 0.22247 1.0002 sp[2] 0.94655 0.00051296 2.3 1934 0.14009 1 sp[3] 0.94083 0.00053252 2.3 1894 0.15655 1.0005 prev[1] 0.26655 0.00077607 1.9 2820 0.11026 1.0022 prev[2] 0.4315 0.0011503 2.2 2084 0.16525 1.0023 prev[3] 0.77007 0.0017624 2.9 1151 0.31792 1.0043 covse_1_2 0.013486 0.00038959 3 1115 0.33293 1.0026 covse_1_3 0.0082942 0.00040511 3.1 1067 0.33178 1.0013 covse_2_3 0.0066393 0.00040915 3 1123 0.34721 1.0028 corse_1_2 0.081424 0.0019917 2.7 1373 0.26665 1.0015 corse_1_3 0.0582 0.0025822 2.7 1386 0.26427 1.0004 corse_2_3 0.05132 0.0028583 2.8 1265 0.27272 1.0016 covsp_1_2 0.00052789 0.000032075 2.1 2165 0.12806 1.0001 covsp_1_3 0.0003108 0.000031064 2.1 2255 0.12438 1.0088 covsp_2_3 0.00092793 0.000039417 2.5 1626 0.22076 0.99996 corsp_1_2 0.021643 0.0022759 1.9 2868 0.086439 1.0002 corsp_1_3 0.022043 0.002406 1.8 3197 0.076892 1.0056 corsp_2_3 0.02581 0.0019243 1.9 2839 0.083759 1.0003 check_outcome_RRR[1,1] 9 0.10952 1.2 7528 0.026051 0.99998 check_outcome_RRR[2,1] -4 0.069828 1.6 3845 0.078595 1.0002 check_outcome_RRR[3,1] -3 0.052477 1.3 5595 0.035268 1 check_outcome_RRR[4,1] 1 0.022698 0.8 17462 0.0025201 0.99995 check_outcome_RRR[5,1] -3 0.056281 1.3 5524 0.044041 0.99999 check_outcome_RRR[6,1] -3 0.023017 0.7 18115 -0.0056044 0.99996 check_outcome_RRR[7,1] 6 0.022901 0.7 18079 0.0017939 0.99999 check_outcome_RRR[8,1] 0 0.040875 0.8 15884 0.0041856 1.0001 check_outcome_RRR[1,2] -2 0.079437 0.8 14683 0.00087038 0.99995 check_outcome_RRR[2,2] 4 0.039815 1 9317 0.023224 1.0002 check_outcome_RRR[3,2] 2 0.034864 1 10480 0.011571 1 check_outcome_RRR[4,2] 2 0.028474 0.8 17703 0.0079894 1.0001 check_outcome_RRR[5,2] -1 0.035191 0.9 12415 0.0053208 0.99999 check_outcome_RRR[6,2] 0 0.031015 0.8 16161 0.0044036 1.0001 check_outcome_RRR[7,2] 1 0.030475 0.8 16435 0.011273 1.0001 check_outcome_RRR[8,2] -2 0.048966 0.8 16410 -0.01674 1 check_outcome_RRR[1,3] 1 0.066354 0.8 15747 -0.00088175 1.0011 check_outcome_RRR[2,3] -1 0.04864 1.2 7463 0.019997 1.0003 check_outcome_RRR[3,3] 0 0.043067 1.1 8729 0.016017 1.0001 check_outcome_RRR[4,3] 2 0.039345 0.8 17067 0.004034 1 check_outcome_RRR[5,3] 0 0.049641 1.1 8243 0.019644 1.0004 check_outcome_RRR[6,3] 7 0.040284 0.8 17192 0.0023538 1.0001 check_outcome_RRR[7,3] -1 0.03998 0.8 17549 0.014847 1.0001 check_outcome_RRR[8,3] -3 0.073571 0.9 12151 0.0058025 1.0002 Total time taken: 16.4 seconds > > template_huiwalter(testdata, outfile="huiwalter_model.txt", covariance=TRUE, cov_as_cor=FALSE) The model and data have been written to huiwalter_model.txt in the current working directory *** NOTE: The template provided should be examined and modified (including checking *** *** priors, covariance terms, and verifying the code) before running the model! *** Warning messages: 1: In template_huiwalter(testdata, outfile = "huiwalter_model.txt", : Setting covariance=TRUE is now deprecated; please specify a data frame of desired covariance terms instead (see ?template_huiwalter) 2: In template_huiwalter(testdata, outfile = "huiwalter_model.txt", : You have specified a lot of active conditional depdendence terms, which is not recommended; if you really need this many conditional depdendence terms then you should probably use an alternative model formulation > results <- run.jags("huiwalter_model.txt") Compiling rjags model... Calling the simulation using the rjags method... Adapting the model for 1000 iterations... Burning in the model for 4000 iterations... Running the model for 10000 iterations... Simulation complete Calculating summary statistics... Calculating the Gelman-Rubin statistic for 45 variables.... Note: Unable to calculate the multivariate psrf Finished running the simulation > #unlink("huiwalter_model.txt") > results JAGS model summary statistics from 20000 samples (chains = 2; adapt+burnin = 5000): Lower95 Median Upper95 Mean SD se[1] 0.59167 0.68206 0.77124 0.68063 0.04595 se[2] 0.58542 0.68046 0.76818 0.67881 0.047351 se[3] 0.61028 0.7071 0.79393 0.70549 0.04756 sp[1] 0.88402 0.93191 0.9762 0.93099 0.023763 sp[2] 0.90224 0.94567 0.98598 0.94463 0.021861 sp[3] 0.88953 0.94021 0.98408 0.9389 0.024339 prev[1] 0.19644 0.27168 0.35604 0.27362 0.040971 prev[2] 0.34183 0.43826 0.54862 0.44103 0.053169 prev[3] 0.67863 0.78321 0.91856 0.78885 0.061161 covse_1_2 -0.0082419 0.015328 0.041322 0.015755 0.012976 covse_1_3 -0.013894 0.0098568 0.036588 0.010353 0.013254 covse_2_3 -0.016139 0.0092427 0.036086 0.009818 0.013718 corse_1_2 -0.082496 0.077499 0.20432 0.071056 0.073349 corse_1_3 -0.17403 0.051795 0.19049 0.036467 0.094021 corse_2_3 -0.19175 0.048223 0.19442 0.030751 0.10014 covsp_1_2 -0.0019661 0.00068839 0.0041453 0.0008491 0.001524 covsp_1_3 -0.0024686 0.00039671 0.0034788 0.00046181 0.001455 covsp_2_3 -0.0015789 0.0011429 0.0045612 0.0013285 0.0015549 corsp_1_2 -0.35025 0.017668 0.13433 -0.023974 0.12412 corsp_1_3 -0.37761 0.0095587 0.11271 -0.049285 0.13452 corsp_2_3 -0.28743 0.030622 0.16113 0.010366 0.10428 check_outcome_RRR[1,1] -8 11 28 10.92 9.3385 check_outcome_RRR[2,1] -15 -5 1 -5.6235 4.2965 check_outcome_RRR[3,1] -12 -4 2 -4.4589 3.8137 check_outcome_RRR[4,1] -6 1 5 0.53745 2.9765 check_outcome_RRR[5,1] -13 -3 3 -3.4123 4.2176 check_outcome_RRR[6,1] -10 -3 2 -2.8385 3.1043 check_outcome_RRR[7,1] -1 5 10 5.1502 3.0764 check_outcome_RRR[8,1] -10 0 9 -0.27485 5.1255 check_outcome_RRR[1,2] -21 -2 16 -1.7063 9.6231 check_outcome_RRR[2,2] -5 3 9 2.8174 3.7823 check_outcome_RRR[3,2] -6 2 7 1.4552 3.5132 check_outcome_RRR[4,2] -6 2 8 1.251 3.8146 check_outcome_RRR[5,2] -10 -1 5 -0.9424 3.9211 check_outcome_RRR[6,2] -9 0 6 -0.37705 3.9346 check_outcome_RRR[7,2] -9 0 6 -0.22875 3.9104 check_outcome_RRR[8,2] -15 -2 9 -2.2692 6.3166 check_outcome_RRR[1,3] -17 0 15 -0.00035 8.2354 check_outcome_RRR[2,3] -10 -2 5 -2.215 4.1412 check_outcome_RRR[3,3] -10 -1 5 -1.6584 4.0158 check_outcome_RRR[4,3] -10 2 10 1.4206 5.1865 check_outcome_RRR[5,3] -10 -1 7 -1.0004 4.5178 check_outcome_RRR[6,3] -5 7 15 6.3038 5.274 check_outcome_RRR[7,3] -12 -1 8 -1.3912 5.2618 check_outcome_RRR[8,3] -18 -1 13 -1.4592 8.0937 Mode MCerr MC%ofSD SSeff AC.10 psrf se[1] 0.68706 0.001357 3 1147 0.3177 1.0028 se[2] 0.68305 0.0014866 3.1 1015 0.34831 1.0025 se[3] 0.70641 0.0014956 3.1 1011 0.35724 1.0021 sp[1] 0.93448 0.00057406 2.4 1713 0.18965 1 sp[2] 0.94763 0.00048371 2.2 2043 0.15326 1.0025 sp[3] 0.94248 0.0006023 2.5 1633 0.20754 1.0023 prev[1] 0.26838 0.00083661 2 2398 0.11775 1.0026 prev[2] 0.43843 0.0013097 2.5 1648 0.2011 1.0036 prev[3] 0.77261 0.0020622 3.4 880 0.37884 1.0026 covse_1_2 0.013851 0.00040024 3.1 1051 0.34477 1.0018 covse_1_3 0.0079775 0.00041128 3.1 1038 0.3505 1.0018 covse_2_3 0.0074523 0.00047091 3.4 849 0.39808 1.0012 corse_1_2 0.078945 0.0019718 2.7 1384 0.2665 1.0018 corse_1_3 0.054704 0.0024617 2.6 1459 0.25433 1.0018 corse_2_3 0.056109 0.0029749 3 1133 0.30362 1.002 covsp_1_2 0.00049924 0.000037727 2.5 1632 0.21421 1.0007 covsp_1_3 0.00035791 0.000033738 2.3 1860 0.16227 1.0022 covsp_2_3 0.0010098 0.000040667 2.6 1462 0.23467 1.0014 corsp_1_2 0.022791 0.0024797 2 2506 0.11379 1.0002 corsp_1_3 0.021262 0.0025809 1.9 2717 0.10655 1.0006 corsp_2_3 0.024117 0.0020282 1.9 2643 0.10112 1.0019 check_outcome_RRR[1,1] 10 0.10551 1.1 7834 0.027153 1.0001 check_outcome_RRR[2,1] -5 0.06253 1.5 4721 0.048616 1 check_outcome_RRR[3,1] -3 0.052042 1.4 5370 0.038418 1.0014 check_outcome_RRR[4,1] 1 0.022957 0.8 16811 0.0026297 1.0001 check_outcome_RRR[5,1] -2 0.068161 1.6 3829 0.085585 1.0003 check_outcome_RRR[6,1] -2 0.023613 0.8 17283 0.0035764 0.99998 check_outcome_RRR[7,1] 6 0.023376 0.8 17319 -0.0044658 1.0006 check_outcome_RRR[8,1] 0 0.039523 0.8 16817 -0.0082648 0.99999 check_outcome_RRR[1,2] 1 0.078151 0.8 15162 0.0050519 1.0003 check_outcome_RRR[2,2] 4 0.04064 1.1 8662 0.020512 1 check_outcome_RRR[3,2] 2 0.033822 1 10789 0.017872 1.0004 check_outcome_RRR[4,2] 2 0.029333 0.8 16911 0.0042941 1.0001 check_outcome_RRR[5,2] 0 0.041561 1.1 8901 0.02234 0.99996 check_outcome_RRR[6,2] 1 0.030755 0.8 16367 0.019423 1.0005 check_outcome_RRR[7,2] 0 0.031077 0.8 15833 0.0031527 1.0001 check_outcome_RRR[8,2] -1 0.054069 0.9 13648 0.012361 1.0004 check_outcome_RRR[1,3] 0 0.066717 0.8 15237 0.00031992 0.99996 check_outcome_RRR[2,3] -1 0.046862 1.1 7809 0.015552 1 check_outcome_RRR[3,3] 0 0.041487 1 9369 0.014367 1 check_outcome_RRR[4,3] 2 0.040541 0.8 16367 0.0072452 0.99999 check_outcome_RRR[5,3] -1 0.04809 1.1 8826 0.005638 1.0002 check_outcome_RRR[6,3] 6 0.04043 0.8 17016 0.0080212 1.0002 check_outcome_RRR[7,3] -1 0.041704 0.8 15919 0.0025327 1.0001 check_outcome_RRR[8,3] -2 0.07534 0.9 11541 0.0095087 1.0001 Total time taken: 14.1 seconds > > template_huiwalter(testdata, outfile="huiwalter_model.txt", covariance=FALSE, cov_as_cor=TRUE) The model and data have been written to huiwalter_model.txt in the current working directory *** NOTE: The template provided should be examined and modified (including checking *** *** priors, covariance terms, and verifying the code) before running the model! *** Warning message: In template_huiwalter(testdata, outfile = "huiwalter_model.txt", : The cov_as_cor option is now deprecated and ignored (i.e. always interpreted as FALSE) > results <- run.jags("huiwalter_model.txt") Compiling rjags model... Calling the simulation using the rjags method... Adapting the model for 1000 iterations... Burning in the model for 4000 iterations... Running the model for 10000 iterations... Simulation complete Calculating summary statistics... Note: The monitored variables 'covse_1_2', 'covse_1_3', 'covse_2_3', 'corse_1_2', 'corse_1_3', 'corse_2_3', 'covsp_1_2', 'covsp_1_3', 'covsp_2_3', 'corsp_1_2', 'corsp_1_3' and 'corsp_2_3' appear to be non-stochastic; they will not be included in the convergence diagnostic Calculating the Gelman-Rubin statistic for 45 variables.... Note: Unable to calculate the multivariate psrf Finished running the simulation > #unlink("huiwalter_model.txt") > results JAGS model summary statistics from 20000 samples (chains = 2; adapt+burnin = 5000): Lower95 Median Upper95 Mean SD Mode se[1] 0.64354 0.70505 0.76983 0.7046 0.032198 0.70397 se[2] 0.63915 0.70294 0.76749 0.7025 0.03307 0.70394 se[3] 0.65467 0.7195 0.78197 0.71926 0.032612 0.72246 sp[1] 0.91981 0.9577 0.99291 0.95702 0.018866 0.95986 sp[2] 0.93765 0.9702 0.99999 0.96855 0.017134 0.97189 sp[3] 0.91689 0.95662 0.9936 0.95567 0.019757 0.95902 prev[1] 0.20429 0.27409 0.34821 0.27511 0.036903 0.27192 prev[2] 0.35882 0.44984 0.5388 0.45021 0.045834 0.44841 prev[3] 0.69342 0.7645 0.83476 0.76332 0.036099 0.76794 covse_1_2 0 0 0 0 0 0 covse_1_3 0 0 0 0 0 0 covse_2_3 0 0 0 0 0 0 corse_1_2 0 0 0 0 0 0 corse_1_3 0 0 0 0 0 0 corse_2_3 0 0 0 0 0 0 covsp_1_2 0 0 0 0 0 0 covsp_1_3 0 0 0 0 0 0 covsp_2_3 0 0 0 0 0 0 corsp_1_2 0 0 0 0 0 0 corsp_1_3 0 0 0 0 0 0 corsp_2_3 0 0 0 0 0 0 check_outcome_RRR[1,1] -13 5 23 5.3228 9.3559 2 check_outcome_RRR[2,1] -11 -3 3 -3.0549 3.7439 -2 check_outcome_RRR[3,1] -9 -2 3 -2.4314 3.3676 -1 check_outcome_RRR[4,1] -6 0 5 0.1908 3.0255 1 check_outcome_RRR[5,1] -9 -1 5 -1.4816 3.8455 -1 check_outcome_RRR[6,1] -10 -3 2 -3.5734 3.2027 -3 check_outcome_RRR[7,1] -2 5 10 4.5921 3.1648 5 check_outcome_RRR[8,1] -10 1 9 0.43575 5.011 0 check_outcome_RRR[1,2] -23 -3 15 -2.6938 9.7946 -3 check_outcome_RRR[2,2] -3 4 10 4.2511 3.4677 5 check_outcome_RRR[3,2] -4 3 8 2.556 3.2309 3 check_outcome_RRR[4,2] -8 1 7 0.4012 3.9436 1 check_outcome_RRR[5,2] -6 1 7 0.77155 3.5821 2 check_outcome_RRR[6,2] -11 -1 5 -1.7576 4.1651 -1 check_outcome_RRR[7,2] -10 -1 5 -1.5818 4.0605 0 check_outcome_RRR[8,2] -15 -2 9 -1.9467 6.2058 0 check_outcome_RRR[1,3] -17 1 15 0.30645 8.2686 2 check_outcome_RRR[2,3] -10 -3 3 -2.9246 3.5027 -3 check_outcome_RRR[3,3] -10 -2 3 -2.2734 3.427 -2 check_outcome_RRR[4,3] -10 1 10 0.74325 5.1995 1 check_outcome_RRR[5,3] -6 1 7 0.37955 3.6065 1 check_outcome_RRR[6,3] -7 5 14 4.9256 5.4118 5 check_outcome_RRR[7,3] -14 -3 6 -2.7942 5.3123 -3 check_outcome_RRR[8,3] -14 2 16 1.6373 7.8918 2 MCerr MC%ofSD SSeff AC.10 psrf se[1] 0.00039229 1.2 6737 0.014653 1 se[2] 0.00041107 1.2 6472 0.00757 0.99998 se[3] 0.0003962 1.2 6775 0.010492 1 sp[1] 0.0002456 1.3 5901 0.023248 1 sp[2] 0.00022673 1.3 5710 0.013771 1 sp[3] 0.00024636 1.2 6431 0.016121 1.0007 prev[1] 0.00040593 1.1 8265 0.0062564 1.0001 prev[2] 0.00060881 1.3 5668 0.019146 1.0002 prev[3] 0.00039844 1.1 8208 0.0067999 1.0007 covse_1_2 -- -- -- -- -- covse_1_3 -- -- -- -- -- covse_2_3 -- -- -- -- -- corse_1_2 -- -- -- -- -- corse_1_3 -- -- -- -- -- corse_2_3 -- -- -- -- -- covsp_1_2 -- -- -- -- -- covsp_1_3 -- -- -- -- -- covsp_2_3 -- -- -- -- -- corsp_1_2 -- -- -- -- -- corsp_1_3 -- -- -- -- -- corsp_2_3 -- -- -- -- -- check_outcome_RRR[1,1] 0.075255 0.8 15456 0.00018038 1.0003 check_outcome_RRR[2,1] 0.0328 0.9 13029 0.0098015 1.0005 check_outcome_RRR[3,1] 0.028834 0.9 13640 0.013926 1.0001 check_outcome_RRR[4,1] 0.022266 0.7 18465 -0.0017165 1.0001 check_outcome_RRR[5,1] 0.032307 0.8 14168 0.000086725 1.0006 check_outcome_RRR[6,1] 0.024476 0.8 17122 0.0037562 0.99996 check_outcome_RRR[7,1] 0.024953 0.8 16086 -0.0010626 0.99999 check_outcome_RRR[8,1] 0.037896 0.8 17485 -0.0026037 1.0001 check_outcome_RRR[1,2] 0.077528 0.8 15961 -0.0076782 1 check_outcome_RRR[2,2] 0.027014 0.8 16478 -0.011972 1.0004 check_outcome_RRR[3,2] 0.02425 0.8 17751 -0.00077196 1 check_outcome_RRR[4,2] 0.031953 0.8 15232 0.0030398 1 check_outcome_RRR[5,2] 0.027528 0.8 16932 0.0089101 1.0002 check_outcome_RRR[6,2] 0.034192 0.8 14839 0.0064286 1.0001 check_outcome_RRR[7,2] 0.031889 0.8 16213 -0.0027037 1.0001 check_outcome_RRR[8,2] 0.046873 0.8 17528 -0.0048388 1.0004 check_outcome_RRR[1,3] 0.066263 0.8 15571 -0.0018519 1.0001 check_outcome_RRR[2,3] 0.026028 0.7 18110 -0.0056087 1.0002 check_outcome_RRR[3,3] 0.02593 0.8 17468 -0.0092491 1 check_outcome_RRR[4,3] 0.042014 0.8 15316 0.0031579 1.0002 check_outcome_RRR[5,3] 0.027169 0.8 17621 0.0027891 1.0001 check_outcome_RRR[6,3] 0.043025 0.8 15821 -0.00026883 1.0001 check_outcome_RRR[7,3] 0.042269 0.8 15795 0.0077237 1 check_outcome_RRR[8,3] 0.073765 0.9 11446 0.002838 0.99996 Total time taken: 9.2 seconds > > template_huiwalter(testdata, outfile="huiwalter_model.txt", covariance=FALSE, cov_as_cor=FALSE) The model and data have been written to huiwalter_model.txt in the current working directory *** NOTE: The template provided should be examined and modified (including checking *** *** priors, covariance terms, and verifying the code) before running the model! *** > results <- run.jags("huiwalter_model.txt") Compiling rjags model... Calling the simulation using the rjags method... Adapting the model for 1000 iterations... Burning in the model for 4000 iterations... Running the model for 10000 iterations... Simulation complete Calculating summary statistics... Note: The monitored variables 'covse_1_2', 'covse_1_3', 'covse_2_3', 'corse_1_2', 'corse_1_3', 'corse_2_3', 'covsp_1_2', 'covsp_1_3', 'covsp_2_3', 'corsp_1_2', 'corsp_1_3' and 'corsp_2_3' appear to be non-stochastic; they will not be included in the convergence diagnostic Calculating the Gelman-Rubin statistic for 45 variables.... Note: Unable to calculate the multivariate psrf Finished running the simulation > #unlink("huiwalter_model.txt") > results JAGS model summary statistics from 20000 samples (chains = 2; adapt+burnin = 5000): Lower95 Median Upper95 Mean SD Mode se[1] 0.64019 0.70378 0.76797 0.70367 0.032899 0.70503 se[2] 0.63595 0.70212 0.76579 0.70176 0.033306 0.70397 se[3] 0.65538 0.7191 0.78111 0.71851 0.032514 0.71942 sp[1] 0.92223 0.95897 0.99493 0.95802 0.018994 0.96178 sp[2] 0.93758 0.97047 0.9999 0.96881 0.017395 0.97287 sp[3] 0.91822 0.957 0.9937 0.95588 0.019552 0.95944 prev[1] 0.20484 0.27501 0.34941 0.27603 0.037096 0.27356 prev[2] 0.36235 0.45103 0.54434 0.4516 0.046692 0.45135 prev[3] 0.69322 0.76403 0.83275 0.76321 0.035617 0.76599 covse_1_2 0 0 0 0 0 0 covse_1_3 0 0 0 0 0 0 covse_2_3 0 0 0 0 0 0 corse_1_2 0 0 0 0 0 0 corse_1_3 0 0 0 0 0 0 corse_2_3 0 0 0 0 0 0 covsp_1_2 0 0 0 0 0 0 covsp_1_3 0 0 0 0 0 0 covsp_2_3 0 0 0 0 0 0 corsp_1_2 0 0 0 0 0 0 corsp_1_3 0 0 0 0 0 0 corsp_2_3 0 0 0 0 0 0 check_outcome_RRR[1,1] -14 5 22 5.2502 9.3887 6 check_outcome_RRR[2,1] -11 -3 3 -2.9144 3.7027 -2 check_outcome_RRR[3,1] -10 -2 3 -2.4183 3.4434 -2 check_outcome_RRR[4,1] -6 0 5 0.1364 3.0648 1 check_outcome_RRR[5,1] -9 -1 5 -1.4876 3.8179 0 check_outcome_RRR[6,1] -10 -3 2 -3.5772 3.204 -2 check_outcome_RRR[7,1] -2 5 10 4.548 3.2032 6 check_outcome_RRR[8,1] -10 1 9 0.46295 4.955 1 check_outcome_RRR[1,2] -22 -2 16 -2.41 9.8791 0 check_outcome_RRR[2,2] -3 5 10 4.3401 3.493 5 check_outcome_RRR[3,2] -4 3 8 2.4913 3.2463 3 check_outcome_RRR[4,2] -8 1 7 0.33735 3.9745 2 check_outcome_RRR[5,2] -6 1 7 0.71715 3.5998 1 check_outcome_RRR[6,2] -11 -2 5 -1.7947 4.1406 0 check_outcome_RRR[7,2] -9 -1 6 -1.6505 4.1241 0 check_outcome_RRR[8,2] -15 -2 9 -2.0307 6.2655 -1 check_outcome_RRR[1,3] -17 0 15 0.23335 8.2472 2 check_outcome_RRR[2,3] -10 -3 3 -2.9047 3.5276 -3 check_outcome_RRR[3,3] -10 -2 3 -2.3268 3.4383 -2 check_outcome_RRR[4,3] -11 1 9 0.72415 5.1752 1 check_outcome_RRR[5,3] -6 1 7 0.35355 3.6178 1 check_outcome_RRR[6,3] -5 5 15 4.9082 5.3429 5 check_outcome_RRR[7,3] -13 -3 7 -2.8112 5.3192 -2 check_outcome_RRR[8,3] -15 2 16 1.8234 7.9886 4 MCerr MC%ofSD SSeff AC.10 psrf se[1] 0.00039279 1.2 7015 0.024448 1.0001 se[2] 0.00043129 1.3 5963 0.015476 1.0005 se[3] 0.00040732 1.3 6372 0.012602 1.0001 sp[1] 0.00025659 1.4 5480 0.015963 1.0003 sp[2] 0.00022388 1.3 6037 0.012335 0.99999 sp[3] 0.00024298 1.2 6475 0.02047 1.0004 prev[1] 0.00043647 1.2 7224 -0.0034034 1.0004 prev[2] 0.00064049 1.4 5315 0.0098211 1 prev[3] 0.00039183 1.1 8263 0.0080368 1 covse_1_2 -- -- -- -- -- covse_1_3 -- -- -- -- -- covse_2_3 -- -- -- -- -- corse_1_2 -- -- -- -- -- corse_1_3 -- -- -- -- -- corse_2_3 -- -- -- -- -- covsp_1_2 -- -- -- -- -- covsp_1_3 -- -- -- -- -- covsp_2_3 -- -- -- -- -- corsp_1_2 -- -- -- -- -- corsp_1_3 -- -- -- -- -- corsp_2_3 -- -- -- -- -- check_outcome_RRR[1,1] 0.074766 0.8 15769 -0.0061403 1.0001 check_outcome_RRR[2,1] 0.032854 0.9 12701 0.0042449 1.0001 check_outcome_RRR[3,1] 0.030105 0.9 13083 0.0041424 0.99997 check_outcome_RRR[4,1] 0.023771 0.8 16623 0.00981 1.0003 check_outcome_RRR[5,1] 0.033682 0.9 12848 0.016334 1.0001 check_outcome_RRR[6,1] 0.026318 0.8 14821 0.0054564 1.0001 check_outcome_RRR[7,1] 0.025688 0.8 15549 -0.0022997 0.99995 check_outcome_RRR[8,1] 0.038453 0.8 16605 -0.010284 1.0001 check_outcome_RRR[1,2] 0.082773 0.8 14245 -0.009108 0.99999 check_outcome_RRR[2,2] 0.026484 0.8 17395 0.0012049 0.99999 check_outcome_RRR[3,2] 0.024421 0.8 17671 0.01054 1.0001 check_outcome_RRR[4,2] 0.03445 0.9 13310 0.0051393 0.99997 check_outcome_RRR[5,2] 0.026839 0.7 17990 -0.0013911 0.99997 check_outcome_RRR[6,2] 0.034879 0.8 14093 -0.00257 0.99995 check_outcome_RRR[7,2] 0.033808 0.8 14880 0.0099573 1 check_outcome_RRR[8,2] 0.048448 0.8 16725 -0.0068306 1.0001 check_outcome_RRR[1,3] 0.065742 0.8 15737 -0.0024283 0.99996 check_outcome_RRR[2,3] 0.027368 0.8 16614 -0.0034492 1.0002 check_outcome_RRR[3,3] 0.025806 0.8 17752 0.010472 0.99999 check_outcome_RRR[4,3] 0.042852 0.8 14585 -0.0037857 1.0001 check_outcome_RRR[5,3] 0.027374 0.8 17466 0.0019383 0.99997 check_outcome_RRR[6,3] 0.042812 0.8 15575 -0.0030161 1 check_outcome_RRR[7,3] 0.042403 0.8 15736 0.010329 1.0003 check_outcome_RRR[8,3] 0.076036 1 11038 0.0038951 1.0001 Total time taken: 9.3 seconds > > proc.time() user system elapsed 46.14 1.87 55.06