Issue #374: Set default to mu ~ 1 as formula (#396)

* Add test of mu ~ 1 working

* Set mu ~ 1 as default

* Improve wording

* Redocument following merge

* Include test of brms::bf(mu ~ 1, sigma ~ 1) producing the same thing as mu ~ 1

* Reword to use mu ~ 1

R/fit.R

@@ -36,7 +36,7 @@ epidist <- function(data, formula, family, prior, backend, fn, ...) {
 #' @method epidist default
 #' @family fit
 #' @export
-epidist.default <- function(data, formula = brms::bf(mu ~ 1),
+epidist.default <- function(data, formula = mu ~ 1,
                             family = "lognormal", prior = NULL,
                             backend = "cmdstanr", fn = brms::brm, ...) {
   epidist_validate(data)

tests/testthat/test-formula.R

@@ -11,7 +11,7 @@ as_string_formula <- function(formula) {
 
 test_that("epidist_formula with default settings produces a brmsformula with the correct intercept only formula", { # nolint: line_length_linter.
   form <- epidist_formula(
-    prep_obs, family = family_lognormal, formula = brms::bf(mu ~ 1, sigma ~ 1)
+    prep_obs, family = family_lognormal, formula = mu ~ 1
   )
   expect_s3_class(form, "brmsformula")
   expect_equal(
@@ -22,6 +22,12 @@ test_that("epidist_formula with default settings produces a brmsformula with the
     as_string_formula(form$pforms$sigma),
     "sigma ~ 1"
   )
+  form_explicit <- epidist_formula(
+    prep_obs, family = family_lognormal, formula = brms::bf(mu ~ 1, sigma ~ 1)
+  )
+  attr(form$pforms$sigma, ".Environment") <- NULL
+  attr(form_explicit$pforms$sigma, ".Environment") <- NULL
+  expect_identical(form, form_explicit)
 })
 
 test_that("epidist_formula with custom formulas produces a brmsformula with correct custom formulas", { # nolint: line_length_linter.

tests/testthat/test-int-latent_individual.R

@@ -47,7 +47,7 @@ test_that("epidist.epidist_latent_individual samples from the prior according to
   epidist_formula <- epidist_formula(
     data = prep_obs,
     family = epidist_family,
-    formula = brms::bf(mu ~ 1, sigma ~ 1)
+    formula = mu ~ 1
   )
   epidist_prior <- epidist_prior(
     data = prep_obs,
@@ -139,7 +139,7 @@ test_that("epidist.epidist_latent_individual Stan code has no syntax errors and
   stancode_gamma <- epidist(
     data = prep_obs_gamma,
     family = stats::Gamma(link = "log"),
-    formula = brms::bf(mu ~ 1, shape ~ 1),
+    formula = mu ~ 1,
     output_dir = fs::dir_create(tempfile()),
     fn = brms::make_stancode
   )
@@ -157,7 +157,7 @@ test_that("epidist.epidist_latent_individual fits and the MCMC converges in the
   fit_gamma <- epidist(
     data = prep_obs_gamma,
     family = stats::Gamma(link = "log"),
-    formula = brms::bf(mu ~ 1, shape ~ 1),
+    formula = mu ~ 1,
     seed = 1,
     silent = 2,
     output_dir = fs::dir_create(tempfile())
@@ -174,7 +174,7 @@ test_that("epidist.epidist_latent_individual recovers the simulation settings fo
   fit_gamma <- epidist(
     data = prep_obs_gamma,
     family = stats::Gamma(link = "log"),
-    formula = brms::bf(mu ~ 1, shape ~ 1),
+    formula = mu ~ 1,
     seed = 1,
     silent = 2,
     output_dir = fs::dir_create(tempfile())

vignettes/ebola.Rmd

@@ -212,13 +212,14 @@ Now we are ready to fit the latent individual model.
 
 We start by fitting a single lognormal distribution to the data. 
 This model assumes that a single distribution describes all delays in the data, regardless of the case's location, sex, or any other covariates.
-To do this, we set `formula = bf(mu ~ 1, sigma ~ 1)` to place an model with only and intercept parameter (i.e. `~ 1` in R formula syntax) on the `mu` and `sigma` parameters of the lognormal distribution.
-This distribution is specified using `family = lognormal()`.
+To do this, we set `formula = mu ~ 1` to place an model with only an intercept parameter (i.e. `~ 1` in R formula syntax) on the `mu` parameter of the lognormal distribution specified using `family = lognormal()`.
+(Note that the lognormal distribution has two distributional parameters `mu` and `sigma`.
+As a model is not explicitly placed on `sigma`, a constant model `sigma ~ 1` is assumed.) 
 
 ```{r}
 fit <- epidist(
   data = obs_prep,
-  formula = bf(mu ~ 1, sigma ~ 1),
+  formula = mu ~ 1,
   family = lognormal(),
   algorithm = "sampling",
   refresh = 0,

vignettes/faq.Rmd

@@ -50,7 +50,7 @@ obs_cens_trunc_samp <- simulate_gillespie(seed = 101) |>
 data <- as_latent_individual(obs_cens_trunc_samp)
 fit <- epidist(
   data,
-  formula = bf(mu ~ 1, sigma ~ 1),
+  formula = mu ~ 1,
   seed = 1
 )
 ```
@@ -108,7 +108,7 @@ family <- "lognormal"
 
 epidist_family <- epidist_family(data, family)
 epidist_formula <- epidist_formula(
-  data, family = epidist_family, formula = bf(mu ~ 1, sigma ~ 1)
+  data, family = epidist_family, formula = mu ~ 1
 )
 
 # NULL here means no replacing priors from the user!
@@ -130,7 +130,7 @@ Here are the distributions on the delay distribution mean and standard deviation
 set.seed(1)
 fit_ppc <- epidist(
   data = data,
-  formula = bf(mu ~ 1, sigma ~ 1),
+  formula = mu ~ 1,
   family = "lognormal",
   sample_prior = "only",
   seed = 1