#' posterior distribution. The prior distribution is the initial belief of the
#' distribution of R0, which is the uninformative uniform distribution with
#' values between zero and \code{kappa}. Users can change the value of
-#' /code{kappa} only (i.e., the prior distribution cannot be changed from the
+#' \code{kappa} only (i.e., the prior distribution cannot be changed from the
#' uniform). As more case counts are observed, the influence of the prior
#' distribution should lessen on the final estimate \code{Rhat}.
#'
#' \code{Rhat} is the estimate of R0 (the posterior mean),
#' \code{posterior} is the posterior distribution of R0 from which
#' alternate estimates can be obtained (see examples), and \code{group}
-#' is an indicator variable (if \code{group=TRUE}, zero values of NT
+#' is an indicator variable (if \code{group == TRUE}, zero values of NT
#' were input and grouping was done to obtain \code{Rhat}). The variable
#' \code{posterior} is returned as a list made up of \code{supp} (the
#' support of the distribution) and \code{pmf} (the probability mass
#'
#' @export
seqB <- function(NT, mu, kappa = 20) {
- if (length(NT) < 2) {
+ if (length(NT) < 2)
print("Warning: length of NT should be at least two.")
- } else {
+ else {
if (min(NT) > 0) {
times <- 1:length(NT)
tau <- diff(times)