update docs

R/create.R

@@ -136,6 +136,7 @@ create_future_rt <- function(future = c("latest", "project", "estimate"),
 #' @description `r lifecycle::badge("stable")`
 #' Takes the output from [rt_opts()] and converts it into a list understood by
 #' stan.
+#'
 #' @param rt A list of options as generated by [rt_opts()] defining Rt
 #' estimation. Defaults to [rt_opts()]. To generate new infections using
 #' the non-mechanistic model instead of the renewal equation model, use

R/deprecated.R

@@ -2,8 +2,7 @@
 #'
 #' @description `r lifecycle::badge("deprecated")`
 #' This function acts as a skeleton for a truncated distribution defined by
-#' model type, maximum value and model parameters. It is designed to be used
-#' with the output from [get_dist()].
+#' model type, maximum value and model parameters.
 #'
 #' @param n Numeric vector, number of samples to take (or days for the
 #' probability density).

R/estimate_infections.R

@@ -59,6 +59,14 @@
 #' Corresponds to the "DEBUG" level from `futile.logger`. See `setup_logging`
 #' for more detailed logging options.
 #'
+#' @param filter_leading_zeros Logical, defaults to TRUE. Should zeros at the
+#' start of the time series be filtered out.
+#'
+#' @param zero_threshold `r lifecycle::badge("experimental")` Numeric defaults
+#' to Inf. Indicates if detected zero cases are meaningful by using a threshold
+#' number of cases based on the 7-day average. If the average is above this
+#' threshold then the zero is replaced using `fill`.
+#'
 #' @export
 #' @return A list of output including: posterior samples, summarised posterior
 #' samples, data used to fit the model, and the fit object itself.
@@ -67,7 +75,10 @@
 #' [estimate_truncation()]
 #' @inheritParams create_stan_args
 #' @inheritParams create_stan_data
+#' @inheritParams create_rt_data
+#' @inheritParams create_backcalc_data
 #' @inheritParams create_gp_data
+#' @inheritParams create_obs_model
 #' @inheritParams fit_model_with_nuts
 #' @inheritParams calc_CrIs
 #' @importFrom data.table data.table copy merge.data.table as.data.table

R/opts.R

@@ -915,6 +915,7 @@ stan_pathfinder_opts <- function(backend = "cmdstanr",
 #' default if using the "rstan" backend, and the default model obtained using
 #' [epinow2_cmdstan_model()] if using the "cmdstanr" backend.
 #'
+#' @param samples Numeric, defaults to 2000. Number of posterior samples.
 #' @param method A character string, defaulting to sampling. Currently supports
 #' MCMC sampling ("sampling") or approximate posterior sampling via
 #' variational inference ("vb") and, as experimental features if the

R/simulate_infections.R

@@ -245,7 +245,7 @@ simulate_infections <- function(R, initial_infections,
 #' @importFrom cli cli_abort
 #' @return A list of output as returned by [estimate_infections()] but based on
 #' results from the specified scenario rather than fitting.
-#' @seealso [dist_spec()] [generation_time_opts()] [delay_opts()] [rt_opts()]
+#' @seealso [generation_time_opts()] [delay_opts()] [rt_opts()]
 #' [estimate_infections()] [trunc_opts()] [stan_opts()] [obs_opts()]
 #' [gp_opts()]
 #' @export

R/simulate_secondary.R

@@ -40,8 +40,7 @@ simulate_secondary <- function(primary,
                                truncation = trunc_opts(),
                                obs = obs_opts(),
                                CrIs = c(0.2, 0.5, 0.9),
-                               backend = "rstan",
-                               ...) {
+                               backend = "rstan") {
   assert_data_frame(primary, any.missing = FALSE)
   assert_subset(c("date", "primary"), colnames(primary))
   assert_date(primary$date)