Calculate Rhat statistics for a hmde_fit object
Examples
# basic usage of hmde_extract_Rhat
hmde_data_template("constant_single_ind",
obs_data = Trout_Size_Data[1:4,])|>
hmde_run(chains = 2, iter = 1000,
verbose = FALSE, show_messages = FALSE) |>
hmde_extract_Rhat()
#>
#> SAMPLING FOR MODEL 'constant_single_ind' NOW (CHAIN 1).
#> Chain 1:
#> Chain 1: Gradient evaluation took 2.8e-05 seconds
#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.28 seconds.
#> Chain 1: Adjust your expectations accordingly!
#> Chain 1:
#> Chain 1:
#> Chain 1: Iteration: 1 / 1000 [ 0%] (Warmup)
#> Chain 1: Iteration: 100 / 1000 [ 10%] (Warmup)
#> Chain 1: Iteration: 200 / 1000 [ 20%] (Warmup)
#> Chain 1: Iteration: 300 / 1000 [ 30%] (Warmup)
#> Chain 1: Iteration: 400 / 1000 [ 40%] (Warmup)
#> Chain 1: Iteration: 500 / 1000 [ 50%] (Warmup)
#> Chain 1: Iteration: 501 / 1000 [ 50%] (Sampling)
#> Chain 1: Iteration: 600 / 1000 [ 60%] (Sampling)
#> Chain 1: Iteration: 700 / 1000 [ 70%] (Sampling)
#> Chain 1: Iteration: 800 / 1000 [ 80%] (Sampling)
#> Chain 1: Iteration: 900 / 1000 [ 90%] (Sampling)
#> Chain 1: Iteration: 1000 / 1000 [100%] (Sampling)
#> Chain 1:
#> Chain 1: Elapsed Time: 0.01 seconds (Warm-up)
#> Chain 1: 0.008 seconds (Sampling)
#> Chain 1: 0.018 seconds (Total)
#> Chain 1:
#>
#> SAMPLING FOR MODEL 'constant_single_ind' NOW (CHAIN 2).
#> Chain 2:
#> Chain 2: Gradient evaluation took 3e-06 seconds
#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.03 seconds.
#> Chain 2: Adjust your expectations accordingly!
#> Chain 2:
#> Chain 2:
#> Chain 2: Iteration: 1 / 1000 [ 0%] (Warmup)
#> Chain 2: Iteration: 100 / 1000 [ 10%] (Warmup)
#> Chain 2: Iteration: 200 / 1000 [ 20%] (Warmup)
#> Chain 2: Iteration: 300 / 1000 [ 30%] (Warmup)
#> Chain 2: Iteration: 400 / 1000 [ 40%] (Warmup)
#> Chain 2: Iteration: 500 / 1000 [ 50%] (Warmup)
#> Chain 2: Iteration: 501 / 1000 [ 50%] (Sampling)
#> Chain 2: Iteration: 600 / 1000 [ 60%] (Sampling)
#> Chain 2: Iteration: 700 / 1000 [ 70%] (Sampling)
#> Chain 2: Iteration: 800 / 1000 [ 80%] (Sampling)
#> Chain 2: Iteration: 900 / 1000 [ 90%] (Sampling)
#> Chain 2: Iteration: 1000 / 1000 [100%] (Sampling)
#> Chain 2:
#> Chain 2: Elapsed Time: 0.012 seconds (Warm-up)
#> Chain 2: 0.011 seconds (Sampling)
#> Chain 2: 0.023 seconds (Total)
#> Chain 2:
#> Warning: There were 2 divergent transitions after warmup. See
#> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
#> to find out why this is a problem and how to eliminate them.
#> Warning: Examine the pairs() plot to diagnose sampling problems
#> Warning: The largest R-hat is NA, indicating chains have not mixed.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#r-hat
#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#bulk-ess
#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#tail-ess
#> ind_y_0 ind_beta global_error_sigma y_hat
#> 1.051978 1.054871 1.124265 1.051978
#> y_hat y_hat y_hat lp__
#> 1.056248 1.058747 1.054932 1.091036