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 five 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.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2017-055.zip
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For attribution, please cite this work as
Mazucheli, et al., "mle.tools: An R Package for Maximum Likelihood Bias Correction", The R Journal, 2017
BibTeX citation
@article{RJ-2017-055,
author = {Mazucheli, Josmar and Menezes, André Felipe B. and Nadarajah, Saralees},
title = {mle.tools: An R Package for Maximum Likelihood Bias Correction},
journal = {The R Journal},
year = {2017},
note = {https://doi.org/10.32614/RJ-2017-055},
doi = {10.32614/RJ-2017-055},
volume = {9},
issue = {2},
issn = {2073-4859},
pages = {268-290}
}