Deploying to gh-pages from @ 30d6677 🚀

Author: jgabry

dev/articles/loo2-elpd.html

@@ -153,7 +153,7 @@ print(fit, pars = "beta")
     beta[2] -0.57       0 0.02 -0.62 -0.59 -0.57 -0.55 -0.52  2467    1
     beta[3] -0.31       0 0.04 -0.38 -0.34 -0.32 -0.29 -0.24  2000    1
 
-    Samples were drawn using NUTS(diag_e) at Wed Dec  3 00:23:24 2025.
+    Samples were drawn using NUTS(diag_e) at Wed Dec  3 18:33:06 2025.
     For each parameter, n_eff is a crude measure of effective sample size,
     and Rhat is the potential scale reduction factor on split chains (at 
     convergence, Rhat=1).

dev/articles/loo2-example.html

@@ -11,7 +11,7 @@ articles:
   loo2-non-factorized: loo2-non-factorized.html
   loo2-weights: loo2-weights.html
   loo2-with-rstan: loo2-with-rstan.html
-last_built: 2025-12-02T23:35Z
+last_built: 2025-12-03T17:44Z
 urls:
   reference: https://mc-stan.org/loo/reference
   article: https://mc-stan.org/loo/articles

dev/articles/loo2-large-data.html

@@ -139,8 +139,8 @@ fit <- stan_glm(kid_score ~ mom_hs + mom_iq, data = kidiq)
 #> 
 #> SAMPLING FOR MODEL 'continuous' NOW (CHAIN 1).
 #> Chain 1: 
-#> Chain 1: Gradient evaluation took 2.3e-05 seconds
-#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.23 seconds.
+#> Chain 1: Gradient evaluation took 2.4e-05 seconds
+#> Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.24 seconds.
 #> Chain 1: Adjust your expectations accordingly!
 #> Chain 1: 
 #> Chain 1: 
@@ -164,8 +164,8 @@ fit <- stan_glm(kid_score ~ mom_hs + mom_iq, data = kidiq)
 #> 
 #> SAMPLING FOR MODEL 'continuous' NOW (CHAIN 2).
 #> Chain 2: 
-#> Chain 2: Gradient evaluation took 9e-06 seconds
-#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.09 seconds.
+#> Chain 2: Gradient evaluation took 1e-05 seconds
+#> Chain 2: 1000 transitions using 10 leapfrog steps per transition would take 0.1 seconds.
 #> Chain 2: Adjust your expectations accordingly!
 #> Chain 2: 
 #> Chain 2: 
@@ -182,15 +182,15 @@ fit <- stan_glm(kid_score ~ mom_hs + mom_iq, data = kidiq)
 #> Chain 2: Iteration: 1800 / 2000 [ 90%]  (Sampling)
 #> Chain 2: Iteration: 2000 / 2000 [100%]  (Sampling)
 #> Chain 2: 
-#> Chain 2:  Elapsed Time: 0.03 seconds (Warm-up)
-#> Chain 2:                0.058 seconds (Sampling)
-#> Chain 2:                0.088 seconds (Total)
+#> Chain 2:  Elapsed Time: 0.031 seconds (Warm-up)
+#> Chain 2:                0.059 seconds (Sampling)
+#> Chain 2:                0.09 seconds (Total)
 #> Chain 2: 
 #> 
 #> SAMPLING FOR MODEL 'continuous' NOW (CHAIN 3).
 #> Chain 3: 
-#> Chain 3: Gradient evaluation took 8e-06 seconds
-#> Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.08 seconds.
+#> Chain 3: Gradient evaluation took 1e-05 seconds
+#> Chain 3: 1000 transitions using 10 leapfrog steps per transition would take 0.1 seconds.
 #> Chain 3: Adjust your expectations accordingly!
 #> Chain 3: 
 #> Chain 3: 
@@ -208,14 +208,14 @@ fit <- stan_glm(kid_score ~ mom_hs + mom_iq, data = kidiq)
 #> Chain 3: Iteration: 2000 / 2000 [100%]  (Sampling)
 #> Chain 3: 
 #> Chain 3:  Elapsed Time: 0.033 seconds (Warm-up)
-#> Chain 3:                0.058 seconds (Sampling)
-#> Chain 3:                0.091 seconds (Total)
+#> Chain 3:                0.059 seconds (Sampling)
+#> Chain 3:                0.092 seconds (Total)
 #> Chain 3: 
 #> 
 #> SAMPLING FOR MODEL 'continuous' NOW (CHAIN 4).
 #> Chain 4: 
-#> Chain 4: Gradient evaluation took 3.1e-05 seconds
-#> Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.31 seconds.
+#> Chain 4: Gradient evaluation took 9e-06 seconds
+#> Chain 4: 1000 transitions using 10 leapfrog steps per transition would take 0.09 seconds.
 #> Chain 4: Adjust your expectations accordingly!
 #> Chain 4: 
 #> Chain 4: 
@@ -232,9 +232,9 @@ fit <- stan_glm(kid_score ~ mom_hs + mom_iq, data = kidiq)
 #> Chain 4: Iteration: 1800 / 2000 [ 90%]  (Sampling)
 #> Chain 4: Iteration: 2000 / 2000 [100%]  (Sampling)
 #> Chain 4: 
-#> Chain 4:  Elapsed Time: 0.031 seconds (Warm-up)
-#> Chain 4:                0.057 seconds (Sampling)
-#> Chain 4:                0.088 seconds (Total)
+#> Chain 4:  Elapsed Time: 0.032 seconds (Warm-up)
+#> Chain 4:                0.058 seconds (Sampling)
+#> Chain 4:                0.09 seconds (Total)
 #> Chain 4: 
 ypred1 <- posterior_predict(fit)
 ypred2 <- posterior_predict(fit)