Loading required package: coda Loading required package: lattice Linked to JAGS 3.4.0 Loaded modules: basemod,bugs Loading required package: boot Attaching package: ‘boot’ The following object is masked from ‘package:lattice’: melanoma Loading required package: MASS Loading required package: segmented mixtools package, version 1.0.1, Released January 2014 This package is based upon work supported by the National Science Foundation under Grant No. SES-0518772. **************** Cleaning data for K2 Simulation JAGS @ 2 Removing 0 of 10 essays for length. Calculating initial values for chain 1 ; K2 Simulation JAGS @ 2 number of iterations= 22 number of iterations= 63 number of iterations= 12 number of iterations= 12 number of iterations= 46 number of iterations= 22 number of iterations= 38 number of iterations= 126 number of iterations= 66 number of iterations= 196 Calculating initial values for chain 2 ; K2 Simulation JAGS @ 2 number of iterations= 23 number of iterations= 59 number of iterations= 11 number of iterations= 17 number of iterations= 28 number of iterations= 16 number of iterations= 26 number of iterations= 110 number of iterations= 39 number of iterations= 90 Calculating initial values for chain 3 ; K2 Simulation JAGS @ 2 number of iterations= 21 number of iterations= 29 number of iterations= 13 number of iterations= 15 number of iterations= 21 number of iterations= 22 One of the variances is going to zero; trying new starting values. number of iterations= 36 number of iterations= 158 number of iterations= 5 number of iterations= 208 Loading Model for K2 Simulation JAGS @ 2 module mix loaded module dic loaded Compiling data graph Resolving undeclared variables Allocating nodes Initializing Reading data back into data table Compiling model graph Resolving undeclared variables Allocating nodes Graph Size: 743 Initializing model Burn in iterations for K2 Simulation JAGS @ 2 **************** Learning hyperparameters for K2 Simulation JAGS @ 2 Attempt 1 Labeling components for level 2 model K2 Simulation JAGS @ 2 Labeling components for alpha0 Labeling components for mu0 Labeling components for tau0 Labeling components for beta0 Labeling components for gamma0 **************** Convergence diagnostics for K2 Simulation JAGS @ 2 Run Number 1 Iterations = 1:5000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 5000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE 1.095e+03 1.045e+01 8.536e-02 1.893e-01 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% 1077 1088 1095 1102 1118 Potential scale reduction factors: Point est. Upper C.I. deviance 1 1.01 deviance 3109.297 Iterations = 1:5000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 5000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE 9.86982 4.16310 0.03399 0.09187 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% 3.803 6.861 9.125 12.254 19.730 Potential scale reduction factors: Point est. Upper C.I. alphaN 1.2 1.57 alphaN 1812.074 Iterations = 1:5000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 5000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE alpha0[1] 0.6107 0.08838 0.0007216 0.002926 alpha0[2] 0.3893 0.08838 0.0007216 0.002926 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% alpha0[1] 0.4239 0.5548 0.6152 0.6729 0.7653 alpha0[2] 0.2347 0.3271 0.3848 0.4452 0.5761 Potential scale reduction factors: Point est. Upper C.I. [1,] 1.4 2.02 alpha0[1] alpha0[2] 679.5818 679.5818 Iterations = 1:5000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 5000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE mu0[1] -0.4796 0.1898 0.001549 0.02978 mu0[2] 0.3980 0.3366 0.002748 0.02935 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% mu0[1] -0.8364 -0.6039 -0.4821 -0.3512 -0.1194 mu0[2] -0.2487 0.1786 0.3825 0.6135 1.0849 Potential scale reduction factors: Point est. Upper C.I. mu0[1] 1.03 1.06 mu0[2] 1.02 1.04 Multivariate psrf 1.01 mu0[1] mu0[2] 49.84302 226.21793 Iterations = 1:5000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 5000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE tau0[1] 1.34594 0.6151 0.005023 0.03276 tau0[2] -0.02348 0.5493 0.004485 0.02616 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% tau0[1] 0.09452 0.9301 1.37498 1.7945 2.410 tau0[2] -1.00467 -0.4068 -0.03913 0.3201 1.124 Potential scale reduction factors: Point est. Upper C.I. tau0[1] 1.47 2.2 tau0[2] 1.26 1.7 Multivariate psrf 1.5 tau0[1] tau0[2] 289.5165 388.5598 Iterations = 1:5000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 5000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE beta0[1] 0.5461 0.1820 0.001486 0.02117 beta0[2] 0.8934 0.2691 0.002197 0.01557 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% beta0[1] 0.2772 0.4221 0.5160 0.6291 0.9848 beta0[2] 0.4667 0.6982 0.8692 1.0515 1.4504 Potential scale reduction factors: Point est. Upper C.I. beta0[1] 1.07 1.23 beta0[2] 1.08 1.22 Multivariate psrf 1.1 beta0[1] beta0[2] 94.35723 334.80673 Iterations = 1:5000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 5000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE gamma0[1] 1.528 0.5730 0.004679 0.02651 gamma0[2] 1.476 0.4321 0.003528 0.02044 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% gamma0[1] 0.5834 1.115 1.508 1.867 2.803 gamma0[2] 0.8217 1.185 1.409 1.694 2.535 Potential scale reduction factors: Point est. Upper C.I. gamma0[1] 1.70 2.72 gamma0[2] 1.06 1.20 Multivariate psrf 1.6 gamma0[1] gamma0[2] 288.1253 424.3324 Chains of length 5000 for K2 Simulation JAGS @ 2 did not converge in run 1 . Maximum Rhat value = 1.597041 . deviance [[ 1 ]] Mean SD Naive SE Time-series SE 1095.7750811 10.6889927 0.1511652 0.3479842 deviance [[ 2 ]] Mean SD Naive SE Time-series SE 1095.1981836 10.3570415 0.1464707 0.2921450 deviance [[ 3 ]] Mean SD Naive SE Time-series SE 1094.4934532 10.2746157 0.1453050 0.3407978 alphaN [[ 1 ]] Mean SD Naive SE Time-series SE 12.03745883 4.51174669 0.06380573 0.19316346 alphaN [[ 2 ]] Mean SD Naive SE Time-series SE 8.55277222 3.38802999 0.04791398 0.13847100 alphaN [[ 3 ]] Mean SD Naive SE Time-series SE 9.01923501 3.60672224 0.05100676 0.13956263 alpha0 [[ 1 ]] Mean SD Naive SE Time-series SE alpha0[1] 0.6720681 0.08002457 0.001131718 0.005158969 alpha0[2] 0.3279319 0.08002457 0.001131718 0.005158969 alpha0 [[ 2 ]] Mean SD Naive SE Time-series SE alpha0[1] 0.5672629 0.07217739 0.001020742 0.004831297 alpha0[2] 0.4327371 0.07217739 0.001020742 0.004831297 alpha0 [[ 3 ]] Mean SD Naive SE Time-series SE alpha0[1] 0.5927394 0.07644878 0.001081149 0.00520436 alpha0[2] 0.4072606 0.07644878 0.001081149 0.00520436 mu0 [[ 1 ]] Mean SD Naive SE Time-series SE mu0[1] -0.4946621 0.2204908 0.003118211 0.07059474 mu0[2] 0.4253686 0.3236603 0.004577247 0.02569580 mu0 [[ 2 ]] Mean SD Naive SE Time-series SE mu0[1] -0.4927538 0.1802216 0.002548718 0.04314143 mu0[2] 0.3567860 0.3032007 0.004287905 0.04977080 mu0 [[ 3 ]] Mean SD Naive SE Time-series SE mu0[1] -0.4512386 0.1604205 0.002268689 0.03371739 mu0[2] 0.4118952 0.3749852 0.005303092 0.06795384 tau0 [[ 1 ]] Mean SD Naive SE Time-series SE tau0[1] 1.8147243 0.4995336 0.007064472 0.04104606 tau0[2] -0.3522395 0.5193604 0.007344865 0.03790720 tau0 [[ 2 ]] Mean SD Naive SE Time-series SE tau0[1] 1.0652638 0.5465692 0.007729656 0.06893445 tau0[2] 0.1701846 0.4677338 0.006614755 0.04563374 tau0 [[ 3 ]] Mean SD Naive SE Time-series SE tau0[1] 1.1578344 0.5030687 0.007114466 0.05676532 tau0[2] 0.1116202 0.5029552 0.007112861 0.05138898 beta0 [[ 1 ]] Mean SD Naive SE Time-series SE beta0[1] 0.6069923 0.1591745 0.002251067 0.02623419 beta0[2] 0.8269622 0.3134933 0.004433465 0.02173561 beta0 [[ 2 ]] Mean SD Naive SE Time-series SE beta0[1] 0.5284737 0.1980740 0.002801190 0.05165379 beta0[2] 0.8821642 0.2161051 0.003056187 0.02721213 beta0 [[ 3 ]] Mean SD Naive SE Time-series SE beta0[1] 0.5028630 0.1701039 0.002405632 0.02598935 beta0[2] 0.9710766 0.2484987 0.003514303 0.03113157 gamma0 [[ 1 ]] Mean SD Naive SE Time-series SE gamma0[1] 1.021378 0.3927976 0.005554997 0.03836519 gamma0[2] 1.336131 0.4315858 0.006103545 0.03415247 gamma0 [[ 2 ]] Mean SD Naive SE Time-series SE gamma0[1] 1.802432 0.4619752 0.006533317 0.04885953 gamma0[2] 1.518821 0.3962879 0.005604357 0.03463245 gamma0 [[ 3 ]] Mean SD Naive SE Time-series SE gamma0[1] 1.760457 0.4810279 0.006802762 0.04964054 gamma0[2] 1.571854 0.4317595 0.006106001 0.03733973 **************** Learning hyperparameters for K2 Simulation JAGS @ 2 Attempt 2 Labeling components for level 2 model K2 Simulation JAGS @ 2 Labeling components for alpha0 Labeling components for mu0 Labeling components for tau0 Labeling components for beta0 Labeling components for gamma0 **************** Convergence diagnostics for K2 Simulation JAGS @ 2 Run Number 2 Iterations = 1:15000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 15000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE 1.095e+03 1.049e+01 4.947e-02 1.190e-01 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% 1076 1087 1094 1101 1117 Potential scale reduction factors: Point est. Upper C.I. deviance 1 1 deviance 7992.12 Iterations = 1:15000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 15000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE 9.8107 4.2212 0.0199 0.0548 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% 3.788 6.741 9.051 12.109 20.004 Potential scale reduction factors: Point est. Upper C.I. alphaN 1.21 1.6 alphaN 5020.615 Iterations = 1:15000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 15000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE alpha0[1] 0.614 0.09035 0.0004259 0.002022 alpha0[2] 0.386 0.09035 0.0004259 0.002022 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% alpha0[1] 0.4079 0.5592 0.622 0.6782 0.7653 alpha0[2] 0.2347 0.3218 0.378 0.4408 0.5921 Potential scale reduction factors: Point est. Upper C.I. [1,] 1.35 1.94 alpha0[1] alpha0[2] 1595.994 1595.994 Iterations = 1:15000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 15000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE mu0[1] -0.4710 0.187 0.0008813 0.01581 mu0[2] 0.4047 0.336 0.0015840 0.01696 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% mu0[1] -0.8262 -0.5931 -0.4768 -0.3507 -0.09951 mu0[2] -0.2639 0.1879 0.4028 0.6200 1.07433 Potential scale reduction factors: Point est. Upper C.I. mu0[1] 1.04 1.14 mu0[2] 1.01 1.03 Multivariate psrf 1.04 mu0[1] mu0[2] 142.8476 608.8338 Iterations = 1:15000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 15000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE tau0[1] 1.37589 0.6141 0.002895 0.01789 tau0[2] -0.03581 0.5693 0.002684 0.01668 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% tau0[1] 0.06316 0.9798 1.40856 1.8335 2.406 tau0[2] -1.04705 -0.4298 -0.05784 0.3112 1.209 Potential scale reduction factors: Point est. Upper C.I. tau0[1] 1.52 2.31 tau0[2] 1.24 1.66 Multivariate psrf 1.51 tau0[1] tau0[2] 912.8168 1028.8626 Iterations = 1:15000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 15000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE beta0[1] 0.5433 0.2007 0.0009459 0.01322 beta0[2] 0.9037 0.2792 0.0013161 0.01093 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% beta0[1] 0.2713 0.4158 0.5063 0.6266 1.038 beta0[2] 0.4598 0.7096 0.8678 1.0589 1.548 Potential scale reduction factors: Point est. Upper C.I. beta0[1] 1.08 1.24 beta0[2] 1.04 1.12 Multivariate psrf 1.09 beta0[1] beta0[2] 218.7415 935.7632 Iterations = 1:15000 Thinning interval = 1 Number of chains = 3 Sample size per chain = 15000 1. Empirical mean and standard deviation for each variable, plus standard error of the mean: Mean SD Naive SE Time-series SE gamma0[1] 1.486 0.5542 0.002613 0.01426 gamma0[2] 1.472 0.4154 0.001958 0.01079 2. Quantiles for each variable: 2.5% 25% 50% 75% 97.5% gamma0[1] 0.5834 1.087 1.457 1.812 2.741 gamma0[2] 0.8484 1.184 1.408 1.691 2.472 Potential scale reduction factors: Point est. Upper C.I. gamma0[1] 1.71 2.75 gamma0[2] 1.06 1.19 Multivariate psrf 1.61 gamma0[1] gamma0[2] 1002.784 1442.620 Chains of length 10000 for K2 Simulation JAGS @ 2 did not converge in run 2 . Maximum Rhat value = 1.606382 . deviance [[ 1 ]] Mean SD Naive SE Time-series SE 1.094771e+03 1.053164e+01 8.599048e-02 1.905231e-01 deviance [[ 2 ]] Mean SD Naive SE Time-series SE 1.094705e+03 1.049136e+01 8.566156e-02 1.962850e-01 deviance [[ 3 ]] Mean SD Naive SE Time-series SE 1.094804e+03 1.045899e+01 8.539731e-02 2.293475e-01 alphaN [[ 1 ]] Mean SD Naive SE Time-series SE 12.05809988 4.62217240 0.03773988 0.10827970 alphaN [[ 2 ]] Mean SD Naive SE Time-series SE 8.54579939 3.46791720 0.02831543 0.08753771 alphaN [[ 3 ]] Mean SD Naive SE Time-series SE 8.82810408 3.52849913 0.02881007 0.08742490 alpha0 [[ 1 ]] Mean SD Naive SE Time-series SE alpha0[1] 0.6756468 0.07377057 0.0006023342 0.002852108 alpha0[2] 0.3243532 0.07377057 0.0006023342 0.002852108 alpha0 [[ 2 ]] Mean SD Naive SE Time-series SE alpha0[1] 0.5757657 0.08167899 0.0006669061 0.003683327 alpha0[2] 0.4242343 0.08167899 0.0006669061 0.003683327 alpha0 [[ 3 ]] Mean SD Naive SE Time-series SE alpha0[1] 0.5905192 0.08102849 0.0006615949 0.003883965 alpha0[2] 0.4094808 0.08102849 0.0006615949 0.003883965 mu0 [[ 1 ]] Mean SD Naive SE Time-series SE mu0[1] -0.5168321 0.1916903 0.001565145 0.03085972 mu0[2] 0.4287133 0.3288118 0.002684737 0.01625198 mu0 [[ 2 ]] Mean SD Naive SE Time-series SE mu0[1] -0.4660937 0.1696659 0.001385316 0.02166663 mu0[2] 0.3621971 0.3201176 0.002613749 0.03070021 mu0 [[ 3 ]] Mean SD Naive SE Time-series SE mu0[1] -0.4301977 0.1885352 0.001539384 0.02877069 mu0[2] 0.4232857 0.3541594 0.002891700 0.03717325 tau0 [[ 1 ]] Mean SD Naive SE Time-series SE tau0[1] 1.8626674 0.4715309 0.003850034 0.02216971 tau0[2] -0.3683696 0.5163862 0.004216275 0.02386522 tau0 [[ 2 ]] Mean SD Naive SE Time-series SE tau0[1] 1.0889166 0.5226394 0.004267333 0.03443542 tau0[2] 0.1645806 0.5035230 0.004111248 0.02911074 tau0 [[ 3 ]] Mean SD Naive SE Time-series SE tau0[1] 1.17609598 0.5261382 0.004295900 0.03468594 tau0[2] 0.09635902 0.5327969 0.004350268 0.03294796 beta0 [[ 1 ]] Mean SD Naive SE Time-series SE beta0[1] 0.6126640 0.2151048 0.001756323 0.02633117 beta0[2] 0.8383284 0.3016427 0.002462902 0.01187642 beta0 [[ 2 ]] Mean SD Naive SE Time-series SE beta0[1] 0.5038039 0.1997923 0.001631297 0.02149014 beta0[2] 0.9157328 0.2561178 0.002091193 0.02108178 beta0 [[ 3 ]] Mean SD Naive SE Time-series SE beta0[1] 0.5135203 0.1653971 0.001350462 0.02042520 beta0[2] 0.9569810 0.2646012 0.002160460 0.02212015 gamma0 [[ 1 ]] Mean SD Naive SE Time-series SE gamma0[1] 0.9958112 0.3625805 0.002960457 0.01715607 gamma0[2] 1.3377642 0.3952800 0.003227447 0.01627439 gamma0 [[ 2 ]] Mean SD Naive SE Time-series SE gamma0[1] 1.774418 0.4672591 0.003815155 0.02846643 gamma0[2] 1.528764 0.3978636 0.003248543 0.01930486 gamma0 [[ 3 ]] Mean SD Naive SE Time-series SE gamma0[1] 1.686762 0.4558979 0.003722391 0.02692506 gamma0[2] 1.549519 0.4193940 0.003424337 0.02027363 MCMC run did not converge, proceeding anyway. Learning parameters for K2 Simulation JAGS @ 2 Labeling components for K2 Simulation JAGS @ 2 Labeling components for pi Labeling components for mu Labeling components for tau Calculating model fit indexes for K2 Simulation JAGS @ 2 lppd pWAIC1 WAIC1 pWAIC2 WAIC2 -529.67962 36.35029 1132.05981 36.35029 1132.05981 lppd lppd.bayes pDIC DIC pDICalt DICalt -547.85476 -602.55799 -109.40644 986.30308 56.65882 1318.43362 Analaysis complete for K2 Simulation JAGS @ 2 > proc.time() user system elapsed 712.919 1.668 714.767