Measurement Error Modelling using MCEM [R package refitME version 1.3.1]

refitME: Measurement Error Modelling using MCEM

Fits measurement error models using Monte Carlo Expectation Maximization (MCEM). For specific details on the methodology, see: Greg C. G. Wei & Martin A. Tanner (1990) A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms, Journal of the American Statistical Association, 85:411, 699-704 <doi:10.1080/01621459.1990.10474930> For more examples on measurement error modelling using MCEM, see the 'RMarkdown' vignette: "'refitME' R-package tutorial".

Version: 1.3.1

Depends: R (≥ 4.4.0)

Imports: MASS, mgcv, VGAM, VGAMdata, caret, expm, mvtnorm, sandwich, stats, dplyr, scales

Published: 2025年04月13日

DOI: 10.32614/CRAN.package.refitME

Author: Jakub Stoklosa ORCID iD [aut, cre], Wenhan Hwang [aut, ctb], David Warton [aut, ctb]

Maintainer: Jakub Stoklosa <j.stoklosa at unsw.edu.au>

License: GPL-2

NeedsCompilation: no

Materials: README

CRAN checks: refitME results

Documentation:

Reference manual: refitME.html , refitME.pdf

Downloads:

Package source: refitME_1.3.1.tar.gz

Windows binaries: r-devel: refitME_1.3.1.zip, r-release: refitME_1.3.1.zip, r-oldrel: refitME_1.3.1.zip

macOS binaries: r-release (arm64): refitME_1.3.1.tgz, r-oldrel (arm64): refitME_1.3.1.tgz, r-release (x86_64): refitME_1.3.1.tgz, r-oldrel (x86_64): refitME_1.3.1.tgz

Old sources: refitME archive

Linking:

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