R Under development (unstable) (2024-02-19 r85946 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(tsnet) > > test_check("tsnet") SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000304 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.04 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.886 seconds (Warm-up) Chain 1: 1.502 seconds (Sampling) Chain 1: 3.388 seconds (Total) Chain 1: The VAR coefficient matrix of the input model is stable. The VAR coefficient matrix of the input model is stable. The VAR coefficient matrix of the input model is not stable. It is recommended to refit the model and to inspect your data. SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000293 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.93 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.257 seconds (Warm-up) Chain 1: 1.624 seconds (Sampling) Chain 1: 3.881 seconds (Total) Chain 1: The VAR coefficient matrix of the input model is stable. SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.00021 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.1 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.251 seconds (Warm-up) Chain 1: 1.729 seconds (Sampling) Chain 1: 3.98 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000284 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.84 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.366 seconds (Warm-up) Chain 1: 2.289 seconds (Sampling) Chain 1: 4.655 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.00033 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.3 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.329 seconds (Warm-up) Chain 1: 2.126 seconds (Sampling) Chain 1: 4.455 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000286 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.86 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.214 seconds (Warm-up) Chain 1: 1.602 seconds (Sampling) Chain 1: 3.816 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000204 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.04 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.191 seconds (Warm-up) Chain 1: 1.655 seconds (Sampling) Chain 1: 3.846 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000205 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.05 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.042 seconds (Warm-up) Chain 1: 1.509 seconds (Sampling) Chain 1: 3.551 seconds (Total) Chain 1: ### Summary of the Norm-Based Comparison Test ### #--- General Summary ---# In the temporal network 2 of the 2 comparisons were significant. In the contemporaneous network 2 of the 2 comparisons were significant. #--- Model-specific Results ---# For mod_a 0 of the reference distances of the temporal network and 0 of the reference distances of the contemporaneous network were larger than the empirical distance. For mod_b 0 of the reference distances of the temporal network and 0 of the reference distances of the contemporaneous network were larger than the empirical distance. SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000294 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.94 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.849 seconds (Warm-up) Chain 1: 1.786 seconds (Sampling) Chain 1: 3.635 seconds (Total) Chain 1: ### Summary of the Bayesian GVAR model ### #--- General Summary ---# Model was estimated using MCMC with 1 chains using 500 iterations each.Warmup was set to 500 iterations. The model was estimated using the IW covariance prior. #--- Parameter Summary ---# The posterior mean of the temporal coefficients is: V1 V2 V3 V1.l1 0.36313920 0.42837107 0.01408909 V2.l1 0.02613061 0.08078402 0.67478388 V3.l1 -0.19944172 0.53603355 0.02842185 Rownames correspond to the independent variable, column names to the dependent variable. The posterior mean of the contemporaneous coefficients is: V1 V2 V3 V1 0.0000000 0.3110431 -0.5452524 V2 0.3110431 0.0000000 -0.3418568 V3 -0.5452524 -0.3418568 0.0000000 Chain 1: ------------------------------------------------------------ Chain 1: EXPERIMENTAL ALGORITHM: Chain 1: This procedure has not been thoroughly tested and may be unstable Chain 1: or buggy. The interface is subject to change. Chain 1: ------------------------------------------------------------ Chain 1: Chain 1: Chain 1: Chain 1: Gradient evaluation took 0.000203 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.03 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Begin eta adaptation. Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation) Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation) Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation) Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation) Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation) Chain 1: Success! Found best value [eta = 1] earlier than expected. Chain 1: Chain 1: Begin stochastic gradient ascent. Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes Chain 1: 100 -690.635 1.000 1.000 Chain 1: 200 -335.409 1.030 1.059 Chain 1: 300 -326.645 0.695 1.000 Chain 1: 400 -324.070 0.523 1.000 Chain 1: 500 -327.462 0.421 0.027 Chain 1: 600 -325.603 0.352 0.027 Chain 1: 700 -323.425 0.302 0.010 Chain 1: 800 -324.214 0.265 0.010 Chain 1: 900 -323.083 0.236 0.008 Chain 1: 1000 -326.597 0.213 0.010 Chain 1: 1100 -326.039 0.114 0.008 Chain 1: 1200 -325.054 0.008 0.007 Chain 1: 1300 -324.508 0.005 0.006 Chain 1: 1400 -322.472 0.005 0.006 Chain 1: 1500 -323.984 0.005 0.005 Chain 1: 1600 -324.672 0.004 0.003 Chain 1: 1700 -324.649 0.004 0.003 Chain 1: 1800 -323.755 0.004 0.003 Chain 1: 1900 -323.591 0.003 0.003 Chain 1: 2000 -322.747 0.003 0.003 Chain 1: 2100 -324.343 0.003 0.003 Chain 1: 2200 -323.036 0.003 0.003 Chain 1: 2300 -323.635 0.003 0.003 Chain 1: 2400 -323.156 0.003 0.003 Chain 1: 2500 -324.399 0.002 0.003 Chain 1: 2600 -323.484 0.002 0.003 Chain 1: 2700 -323.645 0.003 0.003 Chain 1: 2800 -323.407 0.002 0.003 Chain 1: 2900 -323.630 0.002 0.003 Chain 1: 3000 -322.892 0.002 0.002 Chain 1: 3100 -322.954 0.002 0.002 Chain 1: 3200 -322.404 0.002 0.002 Chain 1: 3300 -324.116 0.002 0.002 Chain 1: 3400 -324.297 0.002 0.002 Chain 1: 3500 -324.991 0.002 0.002 Chain 1: 3600 -322.951 0.002 0.002 Chain 1: 3700 -322.894 0.002 0.002 Chain 1: 3800 -323.407 0.002 0.002 Chain 1: 3900 -322.926 0.002 0.002 Chain 1: 4000 -323.542 0.002 0.002 Chain 1: 4100 -323.265 0.002 0.002 Chain 1: 4200 -322.063 0.002 0.002 Chain 1: 4300 -323.240 0.002 0.002 Chain 1: 4400 -323.057 0.002 0.002 Chain 1: 4500 -324.322 0.002 0.002 Chain 1: 4600 -323.289 0.002 0.002 Chain 1: 4700 -323.621 0.002 0.002 Chain 1: 4800 -322.206 0.002 0.003 Chain 1: 4900 -323.083 0.003 0.003 Chain 1: 5000 -322.895 0.002 0.003 Chain 1: 5100 -323.421 0.003 0.003 Chain 1: 5200 -324.446 0.002 0.003 Chain 1: 5300 -322.729 0.003 0.003 Chain 1: 5400 -323.671 0.003 0.003 Chain 1: 5500 -323.027 0.003 0.003 Chain 1: 5600 -324.008 0.003 0.003 Chain 1: 5700 -322.686 0.003 0.003 Chain 1: 5800 -323.273 0.003 0.003 Chain 1: 5900 -323.497 0.003 0.003 Chain 1: 6000 -321.938 0.003 0.003 Chain 1: 6100 -323.602 0.003 0.003 Chain 1: 6200 -323.059 0.003 0.003 Chain 1: 6300 -323.216 0.003 0.003 Chain 1: 6400 -323.277 0.002 0.002 Chain 1: 6500 -323.089 0.002 0.002 Chain 1: 6600 -323.385 0.002 0.002 Chain 1: 6700 -323.167 0.002 0.001 MEDIAN ELBO CONVERGED Chain 1: Chain 1: Drawing a sample of size 500 from the approximate posterior... Chain 1: COMPLETED. ### Summary of the Bayesian GVAR model ### #--- General Summary ---# Model was estimated using variational inference with 500 iterations. The model was estimated using the IW covariance prior. #--- Parameter Summary ---# The posterior mean of the temporal coefficients is: V1 V2 V3 V1.l1 0.38575367 0.4066452 0.03074168 V2.l1 0.03964994 0.0702455 0.69579666 V3.l1 -0.19847841 0.5507020 0.03232217 Rownames correspond to the independent variable, column names to the dependent variable. The posterior mean of the contemporaneous coefficients is: V1 V2 V3 V1 0.0000000 0.3022128 -0.5422099 V2 0.3022128 0.0000000 -0.3516906 V3 -0.5422099 -0.3516906 0.0000000 SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000288 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.88 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 2.137 seconds (Warm-up) Chain 1: 1.469 seconds (Sampling) Chain 1: 3.606 seconds (Total) Chain 1: Chain 1: ------------------------------------------------------------ Chain 1: EXPERIMENTAL ALGORITHM: Chain 1: This procedure has not been thoroughly tested and may be unstable Chain 1: or buggy. The interface is subject to change. Chain 1: ------------------------------------------------------------ Chain 1: Chain 1: Chain 1: Chain 1: Gradient evaluation took 0.000204 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.04 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Begin eta adaptation. Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation) Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation) Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation) Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation) Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation) Chain 1: Success! Found best value [eta = 1] earlier than expected. Chain 1: Chain 1: Begin stochastic gradient ascent. Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes Chain 1: 100 -350.867 1.000 1.000 Chain 1: 200 -324.143 0.541 1.000 Chain 1: 300 -325.472 0.362 0.082 Chain 1: 400 -323.884 0.273 0.082 Chain 1: 500 -326.422 0.220 0.008 Chain 1: 600 -323.813 0.185 0.008 Chain 1: 700 -324.480 0.158 0.008 Chain 1: 800 -328.036 0.140 0.008 Chain 1: 900 -325.428 0.125 0.008 Chain 1: 1000 -323.182 0.114 0.008 Chain 1: 1100 -325.341 0.014 0.008 Chain 1: 1200 -324.262 0.006 0.007 Chain 1: 1300 -323.668 0.006 0.007 Chain 1: 1400 -324.872 0.006 0.007 Chain 1: 1500 -324.206 0.005 0.007 Chain 1: 1600 -322.509 0.005 0.005 Chain 1: 1700 -323.537 0.005 0.005 Chain 1: 1800 -323.166 0.004 0.004 Chain 1: 1900 -323.734 0.004 0.003 Chain 1: 2000 -324.418 0.003 0.003 Chain 1: 2100 -324.511 0.002 0.002 Chain 1: 2200 -323.715 0.002 0.002 Chain 1: 2300 -322.463 0.003 0.002 Chain 1: 2400 -323.648 0.003 0.002 Chain 1: 2500 -323.953 0.002 0.002 Chain 1: 2600 -323.529 0.002 0.002 Chain 1: 2700 -323.795 0.002 0.002 Chain 1: 2800 -323.784 0.002 0.002 Chain 1: 2900 -324.208 0.002 0.001 Chain 1: 3000 -322.409 0.002 0.001 Chain 1: 3100 -324.070 0.003 0.002 Chain 1: 3200 -323.240 0.003 0.003 Chain 1: 3300 -323.346 0.002 0.001 Chain 1: 3400 -323.472 0.002 0.001 Chain 1: 3500 -322.336 0.002 0.001 Chain 1: 3600 -322.920 0.002 0.002 Chain 1: 3700 -323.406 0.002 0.002 Chain 1: 3800 -323.804 0.002 0.002 Chain 1: 3900 -323.184 0.002 0.002 Chain 1: 4000 -322.385 0.002 0.002 Chain 1: 4100 -322.987 0.002 0.002 Chain 1: 4200 -324.123 0.002 0.002 Chain 1: 4300 -324.642 0.002 0.002 Chain 1: 4400 -323.864 0.002 0.002 Chain 1: 4500 -322.881 0.002 0.002 Chain 1: 4600 -323.128 0.002 0.002 Chain 1: 4700 -323.470 0.002 0.002 Chain 1: 4800 -323.338 0.002 0.002 Chain 1: 4900 -323.941 0.002 0.002 Chain 1: 5000 -323.544 0.002 0.002 Chain 1: 5100 -323.426 0.002 0.002 Chain 1: 5200 -322.630 0.002 0.002 Chain 1: 5300 -322.636 0.001 0.001 Chain 1: 5400 -324.300 0.002 0.001 Chain 1: 5500 -323.236 0.002 0.001 Chain 1: 5600 -324.201 0.002 0.002 Chain 1: 5700 -322.806 0.002 0.002 Chain 1: 5800 -323.220 0.002 0.002 Chain 1: 5900 -322.685 0.002 0.002 Chain 1: 6000 -324.234 0.003 0.003 Chain 1: 6100 -323.868 0.003 0.003 Chain 1: 6200 -323.527 0.003 0.003 Chain 1: 6300 -323.197 0.003 0.003 Chain 1: 6400 -323.486 0.002 0.002 Chain 1: 6500 -322.541 0.002 0.002 Chain 1: 6600 -322.860 0.002 0.001 Chain 1: 6700 -323.500 0.002 0.001 Chain 1: 6800 -322.943 0.002 0.002 Chain 1: 6900 -324.602 0.002 0.002 Chain 1: 7000 -323.583 0.002 0.002 Chain 1: 7100 -323.061 0.002 0.002 Chain 1: 7200 -322.989 0.002 0.002 Chain 1: 7300 -322.238 0.002 0.002 Chain 1: 7400 -322.819 0.002 0.002 Chain 1: 7500 -323.476 0.002 0.002 Chain 1: 7600 -323.539 0.002 0.002 Chain 1: 7700 -322.910 0.002 0.002 Chain 1: 7800 -323.512 0.002 0.002 Chain 1: 7900 -322.631 0.002 0.002 Chain 1: 8000 -322.485 0.002 0.002 Chain 1: 8100 -323.055 0.002 0.002 Chain 1: 8200 -322.971 0.002 0.002 Chain 1: 8300 -323.566 0.001 0.002 Chain 1: 8400 -322.416 0.002 0.002 Chain 1: 8500 -322.522 0.001 0.002 Chain 1: 8600 -322.760 0.002 0.002 Chain 1: 8700 -323.142 0.001 0.002 Chain 1: 8800 -323.563 0.001 0.001 Chain 1: 8900 -322.519 0.001 0.001 Chain 1: 9000 -323.583 0.002 0.002 Chain 1: 9100 -322.181 0.002 0.002 Chain 1: 9200 -323.496 0.002 0.003 Chain 1: 9300 -322.389 0.003 0.003 Chain 1: 9400 -322.914 0.002 0.003 Chain 1: 9500 -322.036 0.003 0.003 Chain 1: 9600 -323.868 0.003 0.003 Chain 1: 9700 -322.259 0.003 0.003 Chain 1: 9800 -323.193 0.004 0.003 Chain 1: 9900 -322.631 0.003 0.003 Chain 1: 10000 -324.050 0.004 0.004 Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged. Chain 1: This variational approximation is not guaranteed to be meaningful. Chain 1: Chain 1: Drawing a sample of size 10000 from the approximate posterior... Chain 1: COMPLETED. SAMPLING FOR MODEL 'VAR_LKJ' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.00029 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.9 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.826 seconds (Warm-up) Chain 1: 1.503 seconds (Sampling) Chain 1: 3.329 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000214 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.14 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.693 seconds (Warm-up) Chain 1: 1.608 seconds (Sampling) Chain 1: 3.301 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000206 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.06 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.638 seconds (Warm-up) Chain 1: 1.522 seconds (Sampling) Chain 1: 3.16 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_LKJ_beep' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000163 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.63 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.445 seconds (Warm-up) Chain 1: 1.489 seconds (Sampling) Chain 1: 2.934 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart_beep' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000289 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.89 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.431 seconds (Warm-up) Chain 1: 1.055 seconds (Sampling) Chain 1: 2.486 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000203 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.03 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.687 seconds (Warm-up) Chain 1: 1.6 seconds (Sampling) Chain 1: 3.287 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_LKJ' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.0002 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 1.763 seconds (Warm-up) Chain 1: 1.395 seconds (Sampling) Chain 1: 3.158 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.00034 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.4 seconds. Chain 1: Adjust your expectations accordingly! Chain 1: Chain 1: Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup) Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup) Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling) Chain 1: Iteration: 1000 / 1000 [100%] (Sampling) Chain 1: Chain 1: Elapsed Time: 7.803 seconds (Warm-up) Chain 1: 5.381 seconds (Sampling) Chain 1: 13.184 seconds (Total) Chain 1: [ FAIL 0 | WARN 12 | SKIP 0 | PASS 108 ] [ FAIL 0 | WARN 12 | SKIP 0 | PASS 108 ] > > proc.time() user system elapsed 97.21 1.00 98.21