Calculate Rhat statistics for a hmde_fit object
Examples
# basic usage of hmde_extract_Rhat
hmde_model("constant_single_ind") |>
hmde_assign_data(Trout_Size_Data)|>
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 2e-05 seconds
#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.2 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: 0.054 seconds (Warm-up)
#> Chain 1: 0.036 seconds (Sampling)
#> Chain 1: 0.09 seconds (Total)
#> Chain 1:
#>
#> SAMPLING FOR MODEL 'constant_single_ind' NOW (CHAIN 2).
#> Chain 2:
#> Chain 2: Gradient evaluation took 1.2e-05 seconds
#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.12 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: 0.057 seconds (Warm-up)
#> Chain 2: 0.042 seconds (Sampling)
#> Chain 2: 0.099 seconds (Total)
#> Chain 2:
#> ind_y_0 ind_beta global_error_sigma y_hat
#> 1.017323 1.007018 1.002807 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.005895 1.008050 1.007499 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.005859 1.008361 1.007821 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.006209 1.009006 1.007800 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.009745 1.017323 1.006080 1.008257
#> y_hat y_hat y_hat y_hat
#> 1.007691 1.017323 1.008494 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.017322 1.017323 1.005382 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.005514 1.017323 1.005836 1.007864
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.010454 1.017323 1.006283
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.006221 1.008183 1.007821
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.006346 1.017323 1.006637
#> y_hat y_hat y_hat y_hat
#> 1.008102 1.017323 1.005823 1.008282
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.006167 1.008432 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.006441 1.017323 1.006158 1.008318
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.006189 1.006197 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.008092 1.017323 1.006283 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.004826 1.017323 1.006085 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.006621 1.017323 1.005699 1.008221
#> y_hat y_hat y_hat y_hat
#> 1.008558 1.017323 1.006580 1.008335
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.005990 1.017323 1.007652
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.007452 1.017323 1.008625
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.008276 1.017323 1.008025
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.006189 1.008227 1.007931
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.005109 1.017323 1.009341
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.008482 1.017323 1.006025
#> y_hat y_hat y_hat y_hat
#> 1.008462 1.017323 1.006010 1.008573
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.005401 1.008257 1.008516
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.004876 1.017323 1.005573
#> y_hat y_hat y_hat y_hat
#> 1.006154 1.017323 1.006827 1.008469
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.006200 1.007897 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.014513 1.017323 1.005901 1.008204
#> y_hat y_hat y_hat y_hat
#> 1.017323 1.005791 1.008367 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.005295 1.008354 1.006391 1.017323
#> y_hat y_hat y_hat y_hat
#> 1.005934 1.008175 1.007081 1.017323
#> y_hat y_hat lp__
#> 1.008183 1.007190 1.007485