R/est_param_2.R

In fhernanb/model: This Package Contains Useful Functions for Modeling Regresion

#' Estimation of mean and/or variance for models fitted with gamlss2.
#' 
#' This function estimates parameters like mean, standard deviation for a 
#' gamlss2 object. This function is very useful when the mean or 
#' standard deviation do not match with the parameters
#' \eqn{\mu}, \eqn{\sigma}, \eqn{\nu} and \eqn{\tau}, ..., or some 
#' function of the parameters \eqn{\mu}, \eqn{\sigma}, \eqn{\nu} and \eqn{\tau}.
#' 
#' @param mod a gamlss2 object.
#' @param fun the estimated parameter, by default is mean but can be 
#' changed for sd, var or any statistical function.
#' @param m a number to indicate the number of observations to simulate, 
#' by default its values is 100.
#' @param data the original data frame used to fit the mod.
#' @param newdata a data frame containing new values for the 
#' explanatory variables.
#' @param ... additional parameters for "fun" function.
#' 
#' @example examples/examples_est_param_2.R
#' @return \code{est_param_2} function returns a vector.
#' 
#' @details The function obtains the fitted values for mu, sigma, nu and tau. 
#' The functions simulates m observations and then it obtains the mean/fun 
#' defined by the user.
#' 
#' @importFrom stats predict
#' @export
est_param_2 <- function(mod, fun="mean", m=100, data, newdata=NULL, ...) {
  stopifnot(class(mod) == "gamlss2")
  
  if (is.null(newdata)) {
    fit <- predict(mod)
    fit
  }
  else {
    fit <- NULL
    for (i in mod$family$names) {
      temp <- predict(mod, model=i, data=data, newdata=newdata, type="parameter")
      fit <- cbind(fit, temp)
    }
  }
  # Auxiliar function to simulate
  generator <- function(x) {
    aux <- paste0("r", mod$family$family, "(n=m, ", paste(x, sep="", collapse=", "), ")")
    eval(parse(text=aux))
  }
  
  x <- t(apply(fit, 1, generator))
  return(apply(x, 1, fun, ...))
}