R Under development (unstable) (2024-02-26 r85990 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 0.000475 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.75 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: 2.202 seconds (Warm-up) Chain 1: 2.118 seconds (Sampling) Chain 1: 4.32 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 0.000285 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.85 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: 2.398 seconds (Warm-up) Chain 1: 2.077 seconds (Sampling) Chain 1: 4.475 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 0.000284 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: 2.252 seconds (Warm-up) Chain 1: 2.197 seconds (Sampling) Chain 1: 4.449 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000287 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.87 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: 2.214 seconds (Sampling) Chain 1: 4.58 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' 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: 2.388 seconds (Warm-up) Chain 1: 2.057 seconds (Sampling) Chain 1: 4.445 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: 2.246 seconds (Warm-up) Chain 1: 2.12 seconds (Sampling) Chain 1: 4.366 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000283 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.83 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: 2.353 seconds (Warm-up) Chain 1: 2.192 seconds (Sampling) Chain 1: 4.545 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: 2.47 seconds (Warm-up) Chain 1: 2.214 seconds (Sampling) Chain 1: 4.684 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 0.000404 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.04 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: 2.378 seconds (Warm-up) Chain 1: 1.909 seconds (Sampling) Chain 1: 4.287 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 0.3586070 0.42336696 0.01925952 V2.l1 0.0162580 0.07170992 0.68286924 V3.l1 -0.1956252 0.53766589 0.02932480 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 0.3088611 -0.5463375 V2 0.3088611 0.0000000 -0.3435948 V3 -0.5463375 -0.3435948 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 0.000286 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: 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 -380.324 1.000 1.000 Chain 1: 200 -327.010 0.582 1.000 Chain 1: 300 -328.639 0.389 0.163 Chain 1: 400 -326.644 0.294 0.163 Chain 1: 500 -328.650 0.236 0.006 Chain 1: 600 -324.210 0.199 0.014 Chain 1: 700 -324.775 0.171 0.006 Chain 1: 800 -326.075 0.150 0.006 Chain 1: 900 -327.263 0.134 0.006 Chain 1: 1000 -323.215 0.122 0.006 Chain 1: 1100 -325.228 0.022 0.006 Chain 1: 1200 -324.841 0.006 0.006 Chain 1: 1300 -323.179 0.006 0.006 Chain 1: 1400 -324.064 0.006 0.005 Chain 1: 1500 -323.932 0.005 0.004 Chain 1: 1600 -323.349 0.004 0.004 Chain 1: 1700 -324.584 0.004 0.004 Chain 1: 1800 -324.609 0.004 0.004 Chain 1: 1900 -322.910 0.004 0.004 Chain 1: 2000 -322.860 0.003 0.003 Chain 1: 2100 -323.498 0.002 0.002 Chain 1: 2200 -323.238 0.002 0.002 Chain 1: 2300 -323.391 0.002 0.002 Chain 1: 2400 -323.259 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 0.33725513 0.45338388 0.023396865 V2.l1 0.01233401 0.09576675 0.686124228 V3.l1 -0.18860701 0.52782998 0.000804496 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 0.3137237 -0.5264032 V2 0.3137237 0.0000000 -0.3263439 V3 -0.5264032 -0.3263439 0.0000000 SAMPLING FOR MODEL 'VAR_wishart' 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: 2.432 seconds (Warm-up) Chain 1: 2.34 seconds (Sampling) Chain 1: 4.772 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 0.000291 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.91 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 -347.694 1.000 1.000 Chain 1: 200 -325.591 0.534 1.000 Chain 1: 300 -322.673 0.359 0.068 Chain 1: 400 -325.212 0.271 0.068 Chain 1: 500 -324.486 0.217 0.009 Chain 1: 600 -324.972 0.181 0.009 Chain 1: 700 -324.989 0.156 0.008 Chain 1: 800 -324.494 0.136 0.008 Chain 1: 900 -323.758 0.121 0.002 Chain 1: 1000 -324.627 0.109 0.003 Chain 1: 1100 -323.338 0.010 0.003 Chain 1: 1200 -324.022 0.003 0.002 Chain 1: 1300 -323.348 0.003 0.002 Chain 1: 1400 -323.993 0.002 0.002 Chain 1: 1500 -324.202 0.002 0.002 Chain 1: 1600 -324.318 0.002 0.002 Chain 1: 1700 -323.788 0.002 0.002 Chain 1: 1800 -322.852 0.002 0.002 Chain 1: 1900 -324.277 0.002 0.002 Chain 1: 2000 -323.019 0.002 0.002 Chain 1: 2100 -323.646 0.002 0.002 Chain 1: 2200 -324.055 0.002 0.002 Chain 1: 2300 -322.659 0.002 0.002 Chain 1: 2400 -324.131 0.003 0.003 Chain 1: 2500 -324.106 0.003 0.003 Chain 1: 2600 -323.815 0.003 0.003 Chain 1: 2700 -323.417 0.003 0.003 Chain 1: 2800 -324.216 0.003 0.002 Chain 1: 2900 -324.911 0.002 0.002 Chain 1: 3000 -323.308 0.002 0.002 Chain 1: 3100 -322.691 0.002 0.002 Chain 1: 3200 -323.051 0.002 0.002 Chain 1: 3300 -322.321 0.002 0.002 Chain 1: 3400 -323.760 0.002 0.002 Chain 1: 3500 -323.517 0.002 0.002 Chain 1: 3600 -323.022 0.002 0.002 Chain 1: 3700 -323.415 0.002 0.002 Chain 1: 3800 -322.138 0.002 0.002 Chain 1: 3900 -323.027 0.002 0.002 Chain 1: 4000 -324.038 0.002 0.002 Chain 1: 4100 -322.884 0.002 0.003 Chain 1: 4200 -323.333 0.003 0.003 Chain 1: 4300 -324.962 0.003 0.003 Chain 1: 4400 -323.008 0.003 0.003 Chain 1: 4500 -322.654 0.003 0.003 Chain 1: 4600 -322.605 0.003 0.003 Chain 1: 4700 -323.009 0.003 0.003 Chain 1: 4800 -324.796 0.003 0.003 Chain 1: 4900 -324.015 0.003 0.003 Chain 1: 5000 -323.354 0.003 0.002 Chain 1: 5100 -323.626 0.003 0.002 Chain 1: 5200 -323.495 0.002 0.002 Chain 1: 5300 -323.144 0.002 0.001 Chain 1: 5400 -325.463 0.002 0.001 Chain 1: 5500 -322.923 0.003 0.002 Chain 1: 5600 -324.344 0.003 0.002 Chain 1: 5700 -322.561 0.004 0.004 Chain 1: 5800 -322.646 0.003 0.002 Chain 1: 5900 -323.552 0.003 0.003 Chain 1: 6000 -322.648 0.003 0.003 Chain 1: 6100 -324.186 0.004 0.004 Chain 1: 6200 -323.181 0.004 0.004 Chain 1: 6300 -323.419 0.004 0.004 Chain 1: 6400 -323.575 0.003 0.003 Chain 1: 6500 -323.373 0.003 0.003 Chain 1: 6600 -323.295 0.002 0.003 Chain 1: 6700 -323.199 0.002 0.001 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 0.000538 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 5.38 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: 2.394 seconds (Warm-up) Chain 1: 1.792 seconds (Sampling) Chain 1: 4.186 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000283 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.83 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: 2.617 seconds (Warm-up) Chain 1: 2.265 seconds (Sampling) Chain 1: 4.882 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000492 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 4.92 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: 2.442 seconds (Warm-up) Chain 1: 2.206 seconds (Sampling) Chain 1: 4.648 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_LKJ_beep' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000231 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.31 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: 1.728 seconds (Warm-up) Chain 1: 1.733 seconds (Sampling) Chain 1: 3.461 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart_beep' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000261 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.61 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: 1.817 seconds (Warm-up) Chain 1: 1.772 seconds (Sampling) Chain 1: 3.589 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000319 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.19 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: 2.278 seconds (Warm-up) Chain 1: 1.988 seconds (Sampling) Chain 1: 4.266 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_LKJ' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000283 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.83 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: 2.263 seconds (Warm-up) Chain 1: 2.403 seconds (Sampling) Chain 1: 4.666 seconds (Total) Chain 1: SAMPLING FOR MODEL 'VAR_wishart' NOW (CHAIN 1). Chain 1: Chain 1: Gradient evaluation took 0.000529 seconds Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 5.29 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: 10.76 seconds (Warm-up) Chain 1: 11.248 seconds (Sampling) Chain 1: 22.008 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 123.62 1.23 124.86