mle.tools: An R Package for Maximum Likelihood Bias Correction

Authors

Josmar Mazucheli, Universidade Estadual de Maringá
André Felipe B. Menezes, Universidade Estadual de Maringá
Saralees Nadarajah, University of Manchester

Date of this Version

12-2017

Document Type

Article

Citation

The R Journal (December 2017) 9(2); Editor: Roger Bivand

Comments

Copyright 2017, The R Foundation. Open access material. License: CC BY 4.0

Abstract

Recently, Mazucheli (2017) uploaded the package mle.tools to CRAN. It can be used for bias corrections of maximum likelihood estimates through the methodology proposed by Cox and Snell (1968). The main function of the package, coxsnell.bc(), computes the bias corrected maximum likelihood estimates. Although in general, the bias corrected estimators may be expected to have better sampling properties than the uncorrected estimators, analytical expressions from the formula proposed by Cox and Snell (1968) are either tedious or impossible to obtain. The purpose of this paper is twofolded: to introduce the mle.tools package, especially the coxsnell.bc() function; secondly, to compare, for thirty one continuous distributions, the bias estimates from the coxsnell.bc() function and the bias estimates from analytical expressions available in the literature. We also compare, for f ive distributions, the observed and expected Fisher information. Our numerical experiments show that the functions are efficient to estimate the biases by the Cox-Snell formula and for calculating the observed and expected Fisher information.