R/weibull.R

In ssdtools: Species Sensitivity Distributions

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#' @describeIn ssd_p Cumulative Distribution Function for Weibull Distribution
#' @export
#' @examples
#' 
#' ssd_pweibull(1)
ssd_pweibull <- function(q, shape = 1, scale = 1, lower.tail = TRUE, log.p = FALSE) {
  pdist("weibull", q = q, shape = shape, scale = scale, 
        lower.tail = lower.tail, log.p = log.p)
}

#' @describeIn ssd_q Cumulative Distribution Function for Weibull Distribution
#' @export
#' @examples
#' 
#' ssd_qweibull(0.5)
ssd_qweibull <- function(p, shape = 1, scale = 1, lower.tail = TRUE, log.p = FALSE) {
  qdist("weibull", p = p, shape = shape, scale = scale, 
        lower.tail = lower.tail, log.p = log.p)
}

#' @describeIn ssd_r Random Generation for Weibull Distribution
#' @export
#' @examples
#' 
#' set.seed(50)
#' hist(ssd_rweibull(10000), breaks = 1000)
ssd_rweibull <- function(n, shape = 1, scale = 1, chk = TRUE) {
  rdist("weibull", n = n, shape = shape, scale = scale, chk = chk)
}

sweibull <- function(data, pars = NULL) {
  if(!is.null(pars)) return(pars)
  
  x <- mean_weighted_values(data)
  n <- length(x)
  p <-(1:n-0.3) / (n + 0.4)
  m <- stats::lm(log(-log(1-p)) ~ log(sort(x)))
  
  shape <- m$coefficients[2]
  log_scale <- -m$coefficients[1]/shape
  list(
    log_scale = log_scale,
    log_shape = log(shape)
  )
}

pweibull_ssd <- function(q, shape, scale) {
  if(shape <= 0 || scale <= 0) return(NaN)
  stats::pweibull(q, shape, scale)
}

qweibull_ssd <- function(p, shape, scale) {
  if(shape <= 0 || scale <= 0) return(NaN)
  stats::qweibull(p, shape, scale)
}

rweibull_ssd <- function(n, shape, scale) {
  if(shape <= 0 || scale <= 0) return(rep(NaN, n))
  stats::rweibull(n, shape, scale)
}