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Author: seabbs

dev/articles/approx-inference.html

@@ -203,7 +203,7 @@ paths), it does not appear to be working currently[³](#fn3).
 ``` r
 t <- proc.time()
 fit_pathfinder <- epidist(
-  data = data, algorithm = "pathfinder", draws = 4000, num_paths = 1,
+  data = data, algorithm = "pathfinder", draws = 4000, chains = 1,
   backend = "cmdstanr"
 )
 time_pathfinder <- proc.time() - t

dev/articles/approx-inference.md

@@ -246,7 +246,7 @@ fit <- epidist(
 )
 #> Running MCMC with 2 parallel chains...
 #> Chain 2 finished in 6.4 seconds.
-#> Chain 1 finished in 7.4 seconds.
+#> Chain 1 finished in 7.3 seconds.
 #> 
 #> Both chains finished successfully.
 #> Mean chain execution time: 6.9 seconds.
@@ -300,11 +300,11 @@ fit_sex <- epidist(
   backend = "cmdstanr"
 )
 #> Running MCMC with 2 parallel chains...
-#> Chain 2 finished in 14.9 seconds.
+#> Chain 2 finished in 14.6 seconds.
 #> Chain 1 finished in 15.2 seconds.
 #> 
 #> Both chains finished successfully.
-#> Mean chain execution time: 15.0 seconds.
+#> Mean chain execution time: 14.9 seconds.
 #> Total execution time: 15.3 seconds.
 ```
 
@@ -364,12 +364,12 @@ fit_sex_district <- epidist(
   backend = "cmdstanr"
 )
 #> Running MCMC with 2 parallel chains...
-#> Chain 2 finished in 209.6 seconds.
-#> Chain 1 finished in 221.5 seconds.
+#> Chain 2 finished in 208.2 seconds.
+#> Chain 1 finished in 219.6 seconds.
 #> 
 #> Both chains finished successfully.
-#> Mean chain execution time: 215.6 seconds.
-#> Total execution time: 221.6 seconds.
+#> Mean chain execution time: 213.9 seconds.
+#> Total execution time: 219.8 seconds.
 ```
 
 **As this is a longer running model (~ 2 minutes) we have reduced the

dev/articles/ebola.html

@@ -653,8 +653,8 @@ summary(naive_fit)
 #> 
 #> Regression Coefficients:
 #>                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
-#> Intercept           1.42      0.03     1.35     1.48 1.00     3165     2542
-#> sigma_Intercept    -0.76      0.05    -0.85    -0.65 1.00     3477     2652
+#> Intercept           1.42      0.03     1.35     1.48 1.00     3457     2688
+#> sigma_Intercept    -0.75      0.05    -0.85    -0.66 1.00     3465     2362
 #> 
 #> Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
 #> and Tail_ESS are effective sample size measures, and Rhat is the potential
@@ -762,8 +762,8 @@ summary(marginal_fit)
 #> 
 #> Regression Coefficients:
 #>                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
-#> Intercept           1.55      0.05     1.47     1.64 1.00     1960     2120
-#> sigma_Intercept    -0.69      0.07    -0.82    -0.55 1.00     2018     2124
+#> Intercept           1.55      0.05     1.47     1.65 1.00     2168     2146
+#> sigma_Intercept    -0.70      0.07    -0.82    -0.56 1.00     2021     2436
 #> 
 #> Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
 #> and Tail_ESS are effective sample size measures, and Rhat is the potential
@@ -793,12 +793,12 @@ predicted_parameters <- list(marginal = marginal_fit, naive = naive_fit) |>
 
 head(predicted_parameters)
 #>      model draw index       mu     sigma     mean       sd
-#> 1 marginal    1     1 1.566985 0.4970624 5.422304 2.870597
-#> 2 marginal    2     1 1.564414 0.5330268 5.509494 3.158191
-#> 3 marginal    3     1 1.593435 0.5235678 5.643455 3.169276
-#> 4 marginal    4     1 1.635225 0.5641058 6.015457 3.682090
-#> 5 marginal    5     1 1.606278 0.5821182 5.904467 3.749914
-#> 6 marginal    6     1 1.616848 0.5903586 5.996104 3.871893
+#> 1 marginal    1     1 1.606125 0.4812171 5.595204 2.856172
+#> 2 marginal    2     1 1.518663 0.4693530 5.097801 2.530692
+#> 3 marginal    3     1 1.516017 0.5020221 5.165648 2.765575
+#> 4 marginal    4     1 1.604855 0.5498854 5.789475 3.440074
+#> 5 marginal    5     1 1.525693 0.4404084 5.066616 2.344082
+#> 6 marginal    6     1 1.507987 0.4889513 5.091251 2.645843
 ```
 
 Note that by default

dev/articles/ebola.md

@@ -207,7 +207,7 @@ epidist_diagnostics(fit)
     ## # A tibble: 1 × 8
     ##    time samples max_rhat divergent_transitions per_divergent_transitions
     ##   <dbl>   <dbl>    <dbl>                 <dbl>                     <dbl>
-    ## 1  2.55    1000     1.00                     0                         0
+    ## 1  2.52    1000     1.00                     0                         0
     ## # ℹ 3 more variables: max_treedepth <dbl>, no_at_max_treedepth <int>,
     ## #   per_at_max_treedepth <dbl>