##' Calculate expected number of true transmission pairs
##'
##' This function calculates the expected number true transmission pairs in a sample of size `M`.
##' Assumptions about transmission and linkage (single or multiple) can be specified.
##'
##' @param sensitivity scalar or vector giving the sensitivity of the linkage criteria
##' @param rho scalar or vector giving the proportion of the final outbreak size that is sampled
##' @param M scalar or vector giving the number of cases sampled
##' @param R scalar or vector giving the effective reproductive number of the pathogen (default=NULL)
##' @param assumption a character vector indicating which assumptions about transmission and linkage criteria. Default = `'mtml'`. Accepted arguments are:
##' \enumerate{
##' \item `'stsl'` for the single-transmission single-linkage assumption.
##' \item `'mtsl'` for the multiple-transmission single-linkage assumption.
##' \item `'mtml'` for the multiple-transmission multiple-linkage assumption.
##' }
##'
##' @return scalar or vector giving the expected number of true transmission pairs in the sample
##'
##' @author John Giles, Shirlee Wohl, and Justin Lessler
##'
##' @examples
##' translink_expected_links_true(sensitivity=0.99, rho=0.75, M=100, R=1)
##'
##' @family transmission linkage functions
##'
##' @export
##'
translink_expected_links_true <- function(sensitivity, rho, M, R = NULL, assumption = "mtml") {
if (assumption == "stsl") {
message("Calculating expected number of links assuming single-transmission and single-linkage")
out <- translink_expected_links_true_stsl(sensitivity = sensitivity, rho = rho,
M = M)
} else if (assumption == "mtsl") {
message("Calculating expected number of links assuming multiple-transmission and single-linkage")
out <- translink_expected_links_true_mtsl(sensitivity = sensitivity, rho = rho,
M = M, R = R)
} else if (assumption == "mtml") {
message("Calculating expected number of links assuming multiple-transmission and multiple-linkage")
out <- translink_expected_links_true_mtml(sensitivity = sensitivity, rho = rho,
M = M, R = R)
} else {
stop("Incorrect assumption argument")
}
return(out)
}
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