fix: use minimal fit for pre-compilation instead of empty = TRUE

update() doesn't work on empty brmsfits, so use a minimal fit
(chains = 1, iter = 5) for pre-compilation instead.

Co-authored-by: Sam Abbott <contact@samabbott.co.uk>

Author: seabbs-bot

vignettes/approx-inference.Rmd

@@ -154,16 +154,17 @@ data <- as_epidist_marginal_model(linelist_data)
 
 # Pre-compile the model so compilation time is not included
 # in the timing comparisons
-fit_empty <- epidist(
-  data = data, backend = "cmdstanr", empty = TRUE
+fit_compile <- epidist(
+  data = data, backend = "cmdstanr",
+  chains = 1, iter = 5
 )
 ```
 
 We now perform inference with HMC:
 
 ```{r results='hide'}
 t <- proc.time()
-fit_hmc <- update(fit_empty, chains = 4, iter = 2000)
+fit_hmc <- update(fit_compile, chains = 4, iter = 2000)
 time_hmc <- proc.time() - t
 ```
 
@@ -175,13 +176,13 @@ To match the four Markov chains of length 1000 in HMC above, we then draw 4000 s
 ```{r results='hide'}
 t <- proc.time()
 fit_laplace <- update(
-  fit_empty, algorithm = "laplace", draws = 4000
+  fit_compile, algorithm = "laplace", draws = 4000
 )
 time_laplace <- proc.time() - t
 
 t <- proc.time()
 fit_advi <- update(
-  fit_empty, algorithm = "meanfield", draws = 4000
+  fit_compile, algorithm = "meanfield", draws = 4000
 )
 time_advi <- proc.time() - t
 ```
@@ -191,7 +192,7 @@ For the Pathfinder algorithm we will set `num_paths = 1`.
 ```{r results='hide'}
 t <- proc.time()
 fit_pathfinder <- update(
-  fit_empty, algorithm = "pathfinder", draws = 4000,
+  fit_compile, algorithm = "pathfinder", draws = 4000,
   chains = 1
 )
 time_pathfinder <- proc.time() - t