EstimationTools: Maximum Likelihood Estimation for Probability Functions from Data Sets

Routines for parameter estimation for any probability density or mass function implemented in R via maximum likelihood (ML) given a data set. The main routines 'maxlogL' and 'maxlogLreg' are wrapper functions specifically developed for ML estimation. There are included optimization procedures such as 'nlminb' and 'optim' from base package, and 'DEoptim' Mullen (2011) <doi:10.18637/jss.v040.i06>. Standard errors are estimated with 'numDeriv' Gilbert (2011) <> or the option 'Hessian = TRUE' of 'optim' function.

Version: 2.1.0
Depends: R (≥ 3.0.0), DEoptim, survival, stringr, BBmisc
Imports: Rdpack, utils, stats, numDeriv, boot, matrixStats, autoimage, graphics
Suggests: gamlss.dist, knitr, rmarkdown, AdequacyModel, readr, covr, testthat (≥ 3.0.0), vdiffr, spelling
Published: 2021-03-10
Author: Jaime Mosquera ORCID iD [aut, cre], Freddy Hernandez ORCID iD [ctb]
Maintainer: Jaime Mosquera <jmosquerag at>
License: GPL-3
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: EstimationTools results


Reference manual: EstimationTools.pdf
Vignettes: Bootstrap implementation
Estimation with 'maxlogL' objects
maxlogL: Maximum Likelihood estimation in R


Package source: EstimationTools_2.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): EstimationTools_2.1.0.tgz, r-release (x86_64): EstimationTools_2.1.0.tgz, r-oldrel: EstimationTools_2.1.0.tgz
Old sources: EstimationTools archive


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