.devel/R-old/dp2.estimate.R

In Rexamine/agop: Aggregation Operators and Preordered Sets

## This file is part of the 'agop' library.
##
## Copyright 2013 Marek Gagolewski, Anna Cena
##
## Parts of the code are taken from the 'CITAN' R package by Marek Gagolewski
##
## 'agop' is free software: you can redistribute it and/or modify
## it under the terms of the GNU Lesser General Public License as published by
## the Free Software Foundation, either version 3 of the License, or
## (at your option) any later version.
##
## 'agop' is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU Lesser General Public License for more details.
##
## You should have received a copy of the GNU Lesser General Public License
## along with 'agop'. If not, see <http://www.gnu.org/licenses/>.


invisible(NULL)

# #' Finds the maximum likelihood estimator of the Discretized type II Pareto distribution's
# #' shape parameter \eqn{k} and scale parameter \eqn{s}.
# #'
# #' If X has the Pareto-Type II distribution \eqn{P2(k,s)}
# #' then \code{Y=floor(X)} has the Discretized Pareto-Type II distribution DP2(k,s).
# #'
# #' @title Estimation of shape and scale parameters for the Discretized Pareto-Type II distribution (MLE)
# #' @param x a non-negative numeric vector.
# #' @param kmin lower bound for the shape parameter.
# #' @param kmax upper bound for the shape parameter.
# #' @param smin lower bound for the scale parameter.
# #' @param smax upper bound for the scale parameter.
# #' @return
# #' The list  with the following components is passed as a result:
# #' \tabular{ll}{
# #' \code{k} \tab	the estimated parameter of shape.\cr
# #' \code{s} \tab	the estimated parameter of scale.\cr
# #' }
# #' @export
# #' @seealso \code{\link{ppareto2}}, \code{\link{discrpareto2.mlekestimate}},\cr
# #' \code{\link{discrpareto2.goftest}}
# discrpareto2.mleksestimate <- function(x, kmin=1e-4, kmax=100, smin=1e-4, smax=100)
# {
# 	if (mode(x) != "numeric") stop("'x' should be numeric");
# 	x <- x[!is.na(x)];
# 	n <- length(x);
#
# 	if (n < 2) stop("'x' should be of length at least 2");
# 	if (any(x < 0.0)) stop("'x' should be non-negative");
#
# 	res <- optim(c((kmin+kmax)*0.5,(smin+smax)*0.5), function(p,x,n) {
# 		-n*p[1]*log(p[2])-sum(log((p[2]+x)^(-p[1])-(1+p[2]+x)^(-p[1])))
# 	}, gr=NULL, x, n, method="L-BFGS-B", lower=c(kmin,smin), upper=c(kmax,smax))$par
#
# 	list(k=res[1], s=res[2]);
# }
#
#
# #' Finds the maximum likelihood estimator of the Discretized type II Pareto distribution's
# #' shape parameter \eqn{k} for given scale parameter \eqn{s}.
# #'
# #' If X has the Pareto-Type II distribution \eqn{P2(k,s)}
# #' then \code{Y=floor(X)} has the discretized Pareto-Type II distribution DP2(k,s).
# #'
# #' @title Estimation of shape parameter for the Discretized Pareto-Type II distribution (MLE)
# #' @param x a non-negative numeric vector.
# #' @param s scale parameter, \eqn{s>0}.
# #' @param kmin lower bound for the shape parameter.
# #' @param kmax upper bound for the shape parameter.
# #' @return
# #' A single numeric value is returned, the ML estimator of \eqn{k}.
# #' @export
# #' @seealso \code{\link{ppareto2}}, \code{\link{discrpareto2.mleksestimate}},\cr
# #' \code{\link{discrpareto2.goftest}}
# discrpareto2.mlekestimate <- function(x, s, kmin=1e-4, kmax=100)
# {
# 	if (mode(s) != "numeric" || length(s) != 1 || s <= 0) stop("'s' should be > 0");
#
# 	if (mode(x) != "numeric") stop("'x' should be numeric");
# 	x <- x[!is.na(x)];
# 	n <- length(x);
#
# 	if (n < 2) stop("'x' should be of length at least 2");
# 	if (any(x < 0.0)) stop("'x' should be non-negative");
#
# 	res <- optim((kmin+kmax)*0.5, function(k,x,n,s) {
# 		-n*k*log(s)-sum(log((s+x)^(-k)-(1+s+x)^(-k)))
# 	}, gr=NULL, x, n, s, method="L-BFGS-B", lower=c(kmin), upper=c(kmax))$par
#
# 	res[1];
# }