R/llogis.R

In ssdtools: Species Sensitivity Distributions

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#' @describeIn ssd_p Cumulative Distribution Function for Log-Logistic Distribution
#' @export
#' @examples
#' 
#' ssd_pllogis(1)
ssd_pllogis <- function(q, locationlog = 0, scalelog = 1, lower.tail = TRUE, log.p = FALSE) {
  pdist("logis", q = q,  location = locationlog, scale = scalelog, 
        lower.tail = lower.tail, log.p = log.p, .lgt = TRUE)
}

#' @describeIn ssd_q Cumulative Distribution Function for Log-Logistic Distribution
#' @export
#' @examples
#' 
#' ssd_qllogis(0.5)
ssd_qllogis <- function(p, locationlog = 0, scalelog = 1, lower.tail = TRUE, log.p = FALSE) {
  qdist("logis", p = p,  location = locationlog, scale = scalelog,
        lower.tail = lower.tail, log.p = log.p, .lgt = TRUE)
}

#' @describeIn ssd_r Random Generation for Log-Logistic Distribution
#' @export
#' @examples
#' 
#' set.seed(50)
#' hist(ssd_rllogis(10000), breaks = 1000)
ssd_rllogis <- function(n, locationlog = 0, scalelog = 1, chk = TRUE) {
  rdist("logis", n = n,  location = locationlog, scale = scalelog, .lgt = TRUE, chk = chk)
}

sllogis <- function(data, pars = NULL) {
  if(!is.null(pars)) return(pars)
  
  x <- mean_weighted_values(data)
  
  list(
    locationlog = mean(log(x), na.rm = TRUE),
    log_scalelog = log(pi * sd(log(x), na.rm = TRUE) / sqrt(3))
  )
}

plogis_ssd <- function(q, location, scale) {
  if(scale <= 0) return(NaN)
  stats::plogis(q, location, scale)
}

qlogis_ssd <- function(p, location, scale) {
  if(scale <= 0) return(NaN)
  stats::qlogis(p, location, scale)
}

rlogis_ssd <- function(n, location, scale) {
  if(scale <= 0) return(rep(NaN, n))
  stats::rlogis(n, location, scale)
}