R/invpareto.R

In ssdtools: Species Sensitivity Distributions

#    Copyright 2021 Environment and Climate Change Canada
#
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#       https://www.apache.org/licenses/LICENSE-2.0
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#    distributed under the License is distributed on an "AS IS" BASIS,
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#' @describeIn ssd_p Cumulative Distribution Function for Inverse Pareto Distribution
#' @export
#' @examples
#' 
#' ssd_pinvpareto(1)
ssd_pinvpareto <- function(q, shape = 3, scale = 1, lower.tail = TRUE, log.p = FALSE) {
  pdist("invpareto", q = q, shape = shape, scale = scale, 
        lower.tail = lower.tail, log.p = log.p)
}

#' @describeIn ssd_q Quantile Function for Inverse Pareto Distribution
#' @export
#' @examples
#' 
#' ssd_qinvpareto(0.5)
ssd_qinvpareto <- function(p, shape = 3, scale = 1, lower.tail = TRUE, log.p = FALSE) {
  qdist("invpareto", p = p, shape = shape, scale = scale,
        lower.tail = lower.tail, log.p = log.p)
}

#' @describeIn ssd_r Random Generation for Inverse Pareto Distribution
#' @export
#' @examples
#' 
#' set.seed(50)
#' hist(ssd_rinvpareto(10000), breaks = 1000)
ssd_rinvpareto <- function(n, shape = 3, scale = 1, chk = TRUE) {
  rdist("invpareto", n = n, shape = shape, scale = scale, chk = chk)
}

sinvpareto <- function(data, pars = NULL) {
  scale <- max(data$right)
  shape <- 1/mean(log(scale / data$right))
  
  n <- length(data$right)
  scale <- scale * (shape * n) / (shape * n  - 1)
  shape <- 1/mean(log(scale / data$right))

  spars <- list(log_scale = log(scale), log_shape = log(shape))
  if(!is.null(pars)) { # use new bias corrected order statistic
    pars$log_scale <- spars$log_scale
    return(pars)
  }
  spars
}

minvpareto <- function() {
  list(log_scale = factor(NA))
}

pinvpareto_ssd <- function(q, shape, scale) {
  if(shape <= 0 || scale <= 0) return(NaN)
  pow((q/scale),shape)
}

qinvpareto_ssd <- function(p, shape, scale) {
  if(shape <= 0 || scale <= 0) return(NaN)
  pow(p,1/shape) * scale
}