R Under development (unstable) (2025-06-19 r88329 ucrt) -- "Unsuffered Consequences" Copyright (C) 2025 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 0.000386 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.86 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: 1.898 seconds (Warm-up) Chain 1: 1.734 seconds (Sampling) Chain 1: 3.632 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 0.00025 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.5 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: 1.892 seconds (Warm-up) Chain 1: 1.59 seconds (Sampling) Chain 1: 3.482 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 0.000236 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.36 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: 1.89 seconds (Warm-up) Chain 1: 1.643 seconds (Sampling) Chain 1: 3.533 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000282 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.82 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: 1.863 seconds (Warm-up) Chain 1: 1.856 seconds (Sampling) Chain 1: 3.719 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000238 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.38 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: 2.017 seconds (Warm-up) Chain 1: 1.582 seconds (Sampling) Chain 1: 3.599 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000237 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.37 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: 1.93 seconds (Warm-up) Chain 1: 1.564 seconds (Sampling) Chain 1: 3.494 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000239 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.39 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: 1.951 seconds (Warm-up) Chain 1: 1.61 seconds (Sampling) Chain 1: 3.561 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000241 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.41 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: 1.996 seconds (Warm-up) Chain 1: 1.686 seconds (Sampling) Chain 1: 3.682 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 0.000237 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.37 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: 1.985 seconds (Warm-up) Chain 1: 1.781 seconds (Sampling) Chain 1: 3.766 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 0.36607751 0.43162603 0.01048465 V2.l1 0.01527565 0.06692975 0.68271918 V3.l1 -0.19064957 0.54287155 0.02797082 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 0.3032506 -0.5469754 V2 0.3032506 0.0000000 -0.3422293 V3 -0.5469754 -0.3422293 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 0.000235 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.35 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 -563.004 1.000 1.000 Chain 1: 200 -342.242 0.823 1.000 Chain 1: 300 -323.454 0.568 0.645 Chain 1: 400 -326.310 0.428 0.645 Chain 1: 500 -324.062 0.344 0.058 Chain 1: 600 -328.790 0.289 0.058 Chain 1: 700 -323.599 0.250 0.016 Chain 1: 800 -324.367 0.219 0.016 Chain 1: 900 -324.196 0.195 0.014 Chain 1: 1000 -325.412 0.176 0.014 Chain 1: 1100 -322.789 0.076 0.009 Chain 1: 1200 -324.108 0.012 0.008 Chain 1: 1300 -323.516 0.007 0.007 Chain 1: 1400 -323.460 0.006 0.004 Chain 1: 1500 -323.553 0.005 0.004 Chain 1: 1600 -323.103 0.004 0.002 Chain 1: 1700 -325.287 0.003 0.002 Chain 1: 1800 -324.830 0.003 0.002 Chain 1: 1900 -323.280 0.003 0.004 Chain 1: 2000 -323.779 0.003 0.002 Chain 1: 2100 -322.921 0.002 0.002 Chain 1: 2200 -322.943 0.002 0.002 Chain 1: 2300 -323.775 0.002 0.002 Chain 1: 2400 -324.720 0.002 0.003 Chain 1: 2500 -323.747 0.003 0.003 Chain 1: 2600 -325.030 0.003 0.003 Chain 1: 2700 -323.802 0.003 0.003 Chain 1: 2800 -323.256 0.003 0.003 Chain 1: 2900 -323.098 0.002 0.003 Chain 1: 3000 -323.292 0.002 0.003 Chain 1: 3100 -323.173 0.002 0.003 Chain 1: 3200 -323.199 0.002 0.003 Chain 1: 3300 -323.151 0.002 0.002 Chain 1: 3400 -323.665 0.002 0.002 Chain 1: 3500 -323.695 0.001 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 0.37373588 0.44362161 0.031497620 V2.l1 0.03560118 0.08665438 0.687165750 V3.l1 -0.22091220 0.52697534 0.001340444 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 0.2987395 -0.5427773 V2 0.2987395 0.0000000 -0.3430151 V3 -0.5427773 -0.3430151 0.0000000 SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000237 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.37 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: 1.927 seconds (Warm-up) Chain 1: 1.858 seconds (Sampling) Chain 1: 3.785 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 0.000236 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.36 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 -355.861 1.000 1.000 Chain 1: 200 -328.998 0.541 1.000 Chain 1: 300 -331.661 0.363 0.082 Chain 1: 400 -325.206 0.277 0.082 Chain 1: 500 -325.150 0.222 0.020 Chain 1: 600 -325.586 0.185 0.020 Chain 1: 700 -323.493 0.160 0.008 Chain 1: 800 -323.637 0.140 0.008 Chain 1: 900 -324.024 0.124 0.006 Chain 1: 1000 -325.970 0.113 0.006 Chain 1: 1100 -325.387 0.013 0.006 Chain 1: 1200 -324.367 0.005 0.003 Chain 1: 1300 -323.505 0.004 0.003 Chain 1: 1400 -324.188 0.003 0.002 Chain 1: 1500 -324.258 0.003 0.002 Chain 1: 1600 -322.118 0.003 0.003 Chain 1: 1700 -323.717 0.003 0.003 Chain 1: 1800 -323.802 0.003 0.003 Chain 1: 1900 -323.381 0.003 0.003 Chain 1: 2000 -323.745 0.002 0.002 Chain 1: 2100 -325.231 0.003 0.003 Chain 1: 2200 -322.882 0.003 0.003 Chain 1: 2300 -324.760 0.003 0.005 Chain 1: 2400 -323.299 0.004 0.005 Chain 1: 2500 -322.997 0.004 0.005 Chain 1: 2600 -323.256 0.003 0.005 Chain 1: 2700 -323.425 0.003 0.001 Chain 1: 2800 -325.213 0.003 0.005 Chain 1: 2900 -323.179 0.004 0.005 Chain 1: 3000 -324.271 0.004 0.005 Chain 1: 3100 -322.743 0.004 0.005 Chain 1: 3200 -324.334 0.004 0.005 Chain 1: 3300 -323.667 0.003 0.005 Chain 1: 3400 -323.479 0.003 0.003 Chain 1: 3500 -322.959 0.003 0.003 Chain 1: 3600 -323.204 0.003 0.003 Chain 1: 3700 -324.638 0.003 0.004 Chain 1: 3800 -323.514 0.003 0.003 Chain 1: 3900 -322.849 0.003 0.003 Chain 1: 4000 -323.854 0.003 0.003 Chain 1: 4100 -324.151 0.002 0.002 Chain 1: 4200 -322.689 0.002 0.002 Chain 1: 4300 -322.435 0.002 0.002 Chain 1: 4400 -323.458 0.002 0.003 Chain 1: 4500 -323.753 0.002 0.003 Chain 1: 4600 -323.881 0.002 0.003 Chain 1: 4700 -322.855 0.002 0.003 Chain 1: 4800 -321.982 0.002 0.003 Chain 1: 4900 -323.768 0.003 0.003 Chain 1: 5000 -323.056 0.002 0.003 Chain 1: 5100 -322.926 0.002 0.003 Chain 1: 5200 -323.274 0.002 0.002 Chain 1: 5300 -322.634 0.002 0.002 Chain 1: 5400 -323.866 0.002 0.002 Chain 1: 5500 -322.928 0.002 0.003 Chain 1: 5600 -324.357 0.003 0.003 Chain 1: 5700 -323.044 0.003 0.003 Chain 1: 5800 -323.834 0.003 0.003 Chain 1: 5900 -324.046 0.002 0.002 Chain 1: 6000 -323.286 0.002 0.002 Chain 1: 6100 -322.918 0.002 0.002 Chain 1: 6200 -324.542 0.003 0.003 Chain 1: 6300 -322.648 0.003 0.004 Chain 1: 6400 -323.449 0.003 0.003 Chain 1: 6500 -323.868 0.003 0.002 Chain 1: 6600 -323.085 0.003 0.002 Chain 1: 6700 -322.115 0.003 0.002 Chain 1: 6800 -323.123 0.003 0.002 Chain 1: 6900 -323.121 0.003 0.002 Chain 1: 7000 -323.880 0.003 0.002 Chain 1: 7100 -323.109 0.003 0.002 Chain 1: 7200 -323.987 0.003 0.002 Chain 1: 7300 -322.806 0.002 0.002 Chain 1: 7400 -323.469 0.002 0.002 Chain 1: 7500 -323.924 0.002 0.002 Chain 1: 7600 -323.492 0.002 0.002 Chain 1: 7700 -322.999 0.002 0.002 Chain 1: 7800 -322.784 0.002 0.002 Chain 1: 7900 -322.547 0.002 0.002 Chain 1: 8000 -323.587 0.002 0.002 Chain 1: 8100 -323.211 0.002 0.002 Chain 1: 8200 -323.058 0.002 0.001 Chain 1: 8300 -323.718 0.001 0.001 Chain 1: 8400 -322.942 0.001 0.001 Chain 1: 8500 -323.003 0.001 0.001 Chain 1: 8600 -322.633 0.001 0.001 Chain 1: 8700 -323.071 0.001 0.001 Chain 1: 8800 -322.992 0.001 0.001 Chain 1: 8900 -323.244 0.001 0.001 Chain 1: 9000 -323.155 0.001 0.001 Chain 1: 9100 -323.536 0.001 0.001 Chain 1: 9200 -323.278 0.001 0.001 Chain 1: 9300 -323.168 0.001 0.001 MEAN ELBO CONVERGED MEDIAN ELBO CONVERGED 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 0.000279 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.79 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: 2.074 seconds (Warm-up) Chain 1: 1.709 seconds (Sampling) Chain 1: 3.783 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000239 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.39 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: 1.919 seconds (Warm-up) Chain 1: 1.821 seconds (Sampling) Chain 1: 3.74 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000241 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.41 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: 2.019 seconds (Warm-up) Chain 1: 1.619 seconds (Sampling) Chain 1: 3.638 seconds (Total) Chain 1: Error : Exception: mismatch in dimension declared and found in context; processing stage=data initialization; variable name=Y_future; position=0; dims declared=(0,3); dims found=(1,3) (in 'string', line 18, column 2 to column 34) failed to create the sampler; sampling not done SAMPLING FOR MODEL 'VAR_wishart_beep' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000216 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.16 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: 1.577 seconds (Warm-up) Chain 1: 1.348 seconds (Sampling) Chain 1: 2.925 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000244 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.44 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: 2.077 seconds (Warm-up) Chain 1: 1.933 seconds (Sampling) Chain 1: 4.01 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_LKJ' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000247 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.47 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: 1.874 seconds (Warm-up) Chain 1: 1.749 seconds (Sampling) Chain 1: 3.623 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000445 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.45 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: 9.444 seconds (Warm-up) Chain 1: 9.326 seconds (Sampling) Chain 1: 18.77 seconds (Total) Chain 1: [ FAIL 0 | WARN 14 | SKIP 0 | PASS 108 ] [ FAIL 0 | WARN 14 | SKIP 0 | PASS 108 ] > > proc.time() user system elapsed 102.43 1.29 103.73