fix the bugs identified by CI

NAMESPACE

@@ -73,6 +73,17 @@ importFrom(lubridate,ymd)
 importFrom(posterior,as_draws_list)
 importFrom(posterior,subset_draws)
 importFrom(rlang,sym)
+importFrom(stats,dnbinom)
+importFrom(stats,dweibull)
+importFrom(stats,ecdf)
+importFrom(stats,plogis)
+importFrom(stats,qlogis)
+importFrom(stats,rlnorm)
+importFrom(stats,rnbinom)
+importFrom(stats,rnorm)
+importFrom(stats,rt)
+importFrom(stats,sd)
+importFrom(stats,time)
 importFrom(tidybayes,spread_draws)
 importFrom(tidybayes,stat_halfeye)
 importFrom(tidybayes,stat_slab)

R/data.R

@@ -32,7 +32,7 @@
 #'   \item{site_pop}{The population size of the wastewater catchment area
 #'   represented by the site variable}
 #'   }
-#' @source generate_simulated_data.R
+#' @source vignette_data.R
 "ww_data"
 
 
@@ -66,7 +66,7 @@
 #'   \item{state_pop}{The number of people contributing to the daily hospital
 #'   admissions}
 #'   }
-#' @source generate_simulated_data.R
+#' @source vignette_data.R
 "hosp_data"
 
 #' Example hospital admissions dataset for evaluation
@@ -90,5 +90,29 @@
 #'   \item{state_pop}{The number of people contributing to the daily hospital
 #'   admissions}
 #'   }
-#' @source generate_simulated_data.R
+#' @source vignette_data.R
 "hosp_data_eval"
+
+#' COVID-19 post-Omicron generation interval probability mass function
+#'
+#' \describe{
+#' A vector that sums to 1, with each element representing the daily
+#' probability of secondary onward transmission occurring on that day. The
+#' first element of this vector represents the day after primary transmission
+#' occurred, it is assumed to be impossible for primary and secondary
+#' transmission to occur on the same day.
+#' }
+#' @source covid_pmfs.R
+"generation_interval"
+
+#' COVID-19 time delay distribution from infection to hospital admission
+#'
+#' \describe{
+#' A vector that sums to 1, with each element representing the daily
+#' probabilty of transitioning from infected to hospitalized, conditioned on
+#' being infected and eventually ending up hospitalized. The first element
+#' represents the probability of being infected and admitted to the hospital
+#' on the same day
+#' }
+#' @source covid_pmfs.R
+"inf_to_hosp"

R/generate_simulated_data.R

@@ -66,7 +66,10 @@
 #' # different labs
 #' sim_data <- generate_simulated_data(
 #'   n_sites = 6,
-#'   site = c(rep(1, 4), rep(2, 2))
+#'   site = c(1, 2, 3, 4, 5, 6, 6),
+#'   lab = c(1, 1, 1, 1, 2, 2, 3),
+#'   ww_pop_sites = c(1e5, 4e5, 2e5, 1.5e5, 5e4, 3e5),
+#'   pop_size = 2e6
 #' )
 #' hosp_data <- sim_data$hosp_data
 #' ww_data <- sim_data$ww_data

R/get_stan_data.R

@@ -572,7 +572,7 @@ get_subpop_data <- function(add_auxiliary_site,
 
 #' Get count data integer sizes for stan
 #'
-#' @param input_cout_data a dataframe with the input count data
+#' @param input_count_data a dataframe with the input count data
 #' @param forecast_date string indicating the forecast date
 #' @param forecast_horizon integer indicating the number of days to make a
 #' forecast for

R/utils.R

@@ -132,7 +132,6 @@ convert_to_logsd <- function(mean, sd) {
 #' @export
 #' @examples
 #' to_simplex(c(1, 1, 1))
-#' @noRd
 to_simplex <- function(vector) {
   return(vector / sum(vector))
 }

R/wwinference-package.R

@@ -13,4 +13,6 @@
 #' @importFrom posterior subset_draws as_draws_list
 #' @importFrom fs path_package
 #' @importFrom rlang sym
+#' @importFrom stats dnbinom dweibull ecdf plogis qlogis rlnorm rnbinom rnorm
+#' rt sd time
 NULL