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: | 1.2.1 |
| Depends: | R (≥ 4.1.0) |
| Imports: | MASS, SemiPar, mgcv, VGAM, VGAMdata, caret, expm, mvtnorm, sandwich, stats, dplyr, scales |
| Published: | 2021-06-28 |
| Author: | Jakub Stoklosa 
[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 |
Downloads:
| Reference manual: | refitME.pdf |
| Package source: | refitME_1.2.1.tar.gz |
| Windows binaries: | r-devel: refitME_1.2.1.zip, r-release: refitME_1.2.0.zip, r-oldrel: refitME_1.2.0.zip |
| macOS binaries: | r-release (arm64): refitME_1.2.0.tgz, r-release (x86_64): refitME_1.2.1.tgz, r-oldrel: refitME_1.2.0.tgz |
| Old sources: | refitME archive |
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