diff options
Diffstat (limited to 'R/WP_known.R')
| -rw-r--r-- | R/WP_known.R | 30 |
1 files changed, 13 insertions, 17 deletions
diff --git a/R/WP_known.R b/R/WP_known.R index 40f1ded..6b0e2ea 100644 --- a/R/WP_known.R +++ b/R/WP_known.R @@ -1,27 +1,23 @@ #' WP method background function WP_known #' -#' This is a background/internal function called by \code{WP}. It computes the maximum likelihood estimator of R0 assuming that the serial distribution is known and finite discrete. +#' This is a background/internal function called by \code{WP}. It computes the maximum +#' likelihood estimator of R0 assuming that the serial distribution is known and finite discrete. #' #' @param NT vector of case counts #' @param p discretized version of the serial distribution #' @return The function returns \code{Rhat}, the maximum likelihood estimator of R0. +#' #' @export -# +WP_known <- function(NT, p) { + k <- length(p) + TT <- length(NT) - 1 + mu_t <- rep(0, TT) + + for (i in 1:TT) { + Nt <- NT[i:max(1, i-k+1)] + mu_t[i] <- sum(p[1:min(k, i)] * Nt) + } -WP_known <- function(NT, p){ - - k <- length(p) - TT <- length(NT)-1 - mu_t <- rep(0, TT) - for(i in 1:TT){ - Nt <- NT[i:max(1,i-k+1)] -# print(Nt) -# print(p[1:min(k,i)]) - mu_t[i] <- sum(p[1:min(k,i)]*Nt) - } - Rhat <- sum(NT[-1])/sum(mu_t) + Rhat <- sum(NT[-1]) / sum(mu_t) return(list(Rhat=Rhat)) - } - - |