Refactor seqB

[Rnaught] / R / seq_bayes.R

diff --git a/R/seq_bayes.R b/R/seq_bayes.R
index 2f871211a085f210215abc0dbef8ce1fff6bd764..b25d273276930293c083a988901db7517054c781 100644 (file)
--- a/R/seq_bayes.R
+++ b/R/seq_bayes.R
@@ -45,15 +45,14 @@
 #' @return If `post` is identical to `TRUE`, a list containing the following
 #'   components is returned:
 #'   * `supp` - the support of the posterior distribution of R0
-#'   * `pmf` - the probability mass function of the posterior distribution
+#'   * `pmf` - the probability mass function of the posterior distribution of R0
 #'
 #'   Otherwise, if `post` is identical to `FALSE`, only the estimate of R0 is
 #'   returned. Note that the estimate is equal to `sum(supp * pmf)` (i.e., the
 #'   posterior mean).
 #'
-#' @references
-#' [Bettencourt and Riberio (PloS One, 2008)](
-#' https://doi.org/10.1371/journal.pone.0002185)
+#' @references [Bettencourt and Riberio (PloS One, 2008)](
+#'   https://doi.org/10.1371/journal.pone.0002185)
 #'
 #' @seealso `vignette("seq_bayes_post", package = "Rnaught")` for examples of
 #'   using the posterior distribution.
@@ -74,22 +73,43 @@
 #' # believed to be at most 4.
 #' estimate <- seq_bayes(cases, mu = 1, kappa = 4)
 #'
-#' # Same as above, but return the posterior distribution instead of the
+#' # Same as above, but return the posterior distribution of R0 instead of the
 #' # estimate.
 #' posterior <- seq_bayes(cases, mu = 1, kappa = 4, post = TRUE)
 #'
+#' # Display the support and probability mass function of the posterior.
+#' posterior$supp
+#' posterior$pmf
+#'
 #' # Note that the following always holds:
 #' estimate == sum(posterior$supp * posterior$pmf)
 seq_bayes <- function(cases, mu, kappa = 20, post = FALSE) {
-  if (any(cases == 0)) {
-    times <- which(cases > 0)
-    if (length(times) < 2) {
-      stop("Vector of case counts must contain at least two positive integers.")
-    }
-    cases <- cases[times]
-  } else {
-    times <- seq_along(cases)
+  validate_cases(cases, min_length = 2, min_count = 0)
+  if (!is_real(mu) || mu <= 0) {
+    stop("The serial interval (`mu`) must be a number greater than 0.",
+      call. = FALSE
+    )
+  }
+  if (!is_real(kappa) || kappa < 1) {
+    stop(
+      paste("The largest value of the uniform prior (`kappa`)",
+        "must be a number greater than or equal to 1."
+      ), call. = FALSE
+    )
+  }
+  if (!identical(post, TRUE) && !identical(post, FALSE)) {
+    stop("The posterior flag (`post`) must be set to `TRUE` or `FALSE`.",
+      call. = FALSE
+    )
+  }
+
+  times <- which(cases > 0)
+  if (length(times) < 2) {
+    stop("Case counts must contain at least two positive integers.",
+      call. = FALSE
+    )
   }
+  cases <- cases[times]
 
   support <- seq(0, kappa, 0.01)
   tau <- diff(times)