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 For more examples on measurement error modelling using MCEM, see the 'RMarkdown' vignette: "'refitME' R-package tutorial".


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install.packages("refitME")

1.2.0 by Jakub Stoklosa, 22 days ago


Browse source code at https://github.com/cran/refitME


Authors: Jakub Stoklosa [aut, cre] , Wenhan Hwang [aut, ctb] , David Warton [aut, ctb] , Jeremy Vanderwal [ctb] (Used the wt.var() function written by Jeremy VanDerWal)


Documentation:   PDF Manual  


GPL-2 license


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


See at CRAN