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Issue #374: Add test of input mu ~ 1 as formula #396

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Issue #374: Add test of input mu ~ 1 as formula #396

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443fb7b
Add package links
athowes Oct 17, 2024
97e166a
Add test of mu ~ 1 working
athowes Oct 18, 2024
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15 changes: 15 additions & 0 deletions tests/testthat/test-formula.R
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Original file line number Diff line number Diff line change
Expand Up @@ -42,6 +42,21 @@ test_that("epidist_formula with custom formulas produces a brmsformula with corr
)
})

test_that("epidist_formula with input as a formula (not using brms::bf) produces a brmsformula", { # nolint: line_length_linter.
form <- epidist_formula(
prep_obs, family = family_lognormal, formula = mu ~ 1
)
expect_s3_class(form, "brmsformula")
expect_equal(
as_string_formula(form$formula),
"delay | vreal(relative_obs_time, pwindow, swindow) ~ 1"
)
expect_equal(
as_string_formula(form$pforms$sigma),
"sigma ~ 1"
)
})

test_that("epidist_formula with custom formulas errors for incorrect custom formulas", { # nolint: line_length_linter.
expect_error(
epidist_formula(
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10 changes: 5 additions & 5 deletions vignettes/faq.Rmd
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Expand Up @@ -57,7 +57,7 @@ fit <- epidist(
## I would like to work with the samples output

The output of a call to `epidist` is compatible with typical Stan workflows.
We recommend use of the `posterior` package for working with samples from MCMC or other sampling algorithms.
We recommend use of the [`posterior`](https://mc-stan.org/posterior/) package for working with samples from MCMC or other sampling algorithms.
For example, the function `posterior::as_draws_df()` may be used to obtain a dataframe of MCMC draws for specified parameters.

```{r message = FALSE}
Expand All @@ -69,7 +69,7 @@ head(draws)
## How can I assess if sampling has converged?

The output of a call to `epidist` is compatible with typical Stan workflows.
We recommend use of the `bayesplot` package for sampling diagnostic plots.
We recommend use of the [`bayesplot`](http://mc-stan.org/bayesplot/) package for sampling diagnostic plots.
For example, the function `bayesplot::mcmc_trace()` can be used to produce traceplots for specified parameters.

```{r message = FALSE}
Expand All @@ -85,7 +85,7 @@ epidist_diagnostics(fit)

## I'd like to run a simulation study

We recommend use of the `purrr` package for running many `epidist` models, for example as a part of a simulation study.
We recommend use of the [`purrr`](https://purrr.tidyverse.org/) package for running many `epidist` models, for example as a part of a simulation study.
We particularly highlight two functions which might be useful:

1. `purrr::map()` (and other similar functions) for iterating over a list of inputs.
Expand All @@ -96,7 +96,7 @@ For an example use of these functions, have a look at the [`epidist-paper`](http

## How did you choose the default priors for `epidist`?

`brms` provides default priors for all parameters.
[`brms`](http://paulbuerkner.com/brms/) provides default priors for all parameters.
However, some of those priors do not make sense in the context of our application.
Instead, we used [prior predictive checking](https://mc-stan.org/docs/stan-users-guide/posterior-predictive-checks.html) to set `epidist`-specific default priors which produce epidemiological delay distribution mean and standard deviation parameters in a reasonable range.

Expand Down Expand Up @@ -170,7 +170,7 @@ powerscale_plot_dens(fit, variable = c("Intercept", "Intercept_sigma")) +

# What do the parameters in my model output correspond to?

The `epidist` package uses `brms` to fit models.
The `epidist` package uses [`brms`](http://paulbuerkner.com/brms/) to fit models.
This means that the model output will include `brms`-style names for parameters.
Here, we provide a table giving the correspondence between the distributional parameter names used in `brms` and those used in standard R functions for some common likelihood families.

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