Update docs

[Rnaught] / R / seq_bayes.R

diff --git a/R/seq_bayes.R b/R/seq_bayes.R
index 2f871211a085f210215abc0dbef8ce1fff6bd764..d486d2b8e439e34436fb3919345a56c79066f543 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
 #' @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).
 #'
 #'
 #'   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.
 #'
 #' @seealso `vignette("seq_bayes_post", package = "Rnaught")` for examples of
 #'   using the posterior distribution.


@@ -74,10 +73,14 @@
 #' # believed to be at most 4.
 #' estimate <- seq_bayes(cases, mu = 1, kappa = 4)
 #'
 #' # 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)
 #'
 #' # 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) {
 #' # Note that the following always holds:
 #' estimate == sum(posterior$supp * posterior$pmf)
 seq_bayes <- function(cases, mu, kappa = 20, post = FALSE) {