R Under development (unstable) (2024-12-03 r87418 ucrt) -- "Unsuffered Consequences"
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> ##
> ## spatial econometric models and model comparison with DIC, WAIC, and model probabilities. N = 520
> ##
> 
> #devtools::load_all("~/dev/geostan")
> 
> library(geostan)
This is geostan version 0.8.1
> 
> row = 12
> col = 26
> N <- row * col
> sdl <- prep_sar_data2(row = row, col = col, quiet = TRUE)
> w <- sdl$W
> x <- sim_sar(w = w, rho = .5)
> mu = (.5 * x - .25 * w %*% w)[,1]
> y <- sim_sar(w = w, rho = .5, mu = mu)
> df <- data.frame(y=y, x=x)
> 
> iter = 175
> 
> sdlm <- stan_sar(y ~ x,
+                 data = df,
+                 type = "SDLM",
+                 sar_parts = sdl,
+                 chains = 1,
+                 iter = iter,
+                 quiet = TRUE,
+                 keep_all = TRUE,
+                 slim = F)
Warning messages:
1: The largest R-hat is 1.05, indicating chains have not mixed.
Running the chains for more iterations may help. See
https://mc-stan.org/misc/warnings.html#r-hat 
2: 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 
3: 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 
> 
> sdem <- stan_sar(y ~ x,
+                  data = df,
+                  type = "SDEM",
+                  sar_parts = sdl,
+                  chains = 1,
+                  iter = iter,
+                  quiet = TRUE,
+                 keep_all = TRUE,                 
+                 slim = F) 
Warning messages:
1: 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 
2: 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 
> 
> print(rbind(dic(sdlm), dic(sdem)))
       DIC penalty
[1,] 899.7     4.3
[2,] 900.2     4.8
> print(rbind(waic(sdlm), waic(sdem)))
       WAIC Eff_pars     Lpd
[1,] 898.21     2.17 -446.94
[2,] 898.63     2.39 -446.93
> 
> 
>   #  library(bridgesampling)
>   #  sdlm <- bridge_sampler(sdlm$stanfit)
>   #  sdem <- bridge_sampler(sdem$stanfit)
>   #  cat("post_prob (SDLM, SDEM):\n", post_prob(sdlm, sdem), "\n")
> 
> 
> proc.time()
   user  system elapsed 
   7.78    0.43    8.17