Package: refitME 1.2.2

Jakub Stoklosa

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".

Authors:Jakub Stoklosa [aut, cre], Wenhan Hwang [aut, ctb], David Warton [aut, ctb]

refitME_1.2.2.tar.gz
refitME_1.2.2.tar.gz(r-4.5-noble)refitME_1.2.2.tar.gz(r-4.4-noble)
refitME_1.2.2.tgz(r-4.4-emscripten)refitME_1.2.2.tgz(r-4.3-emscripten)
refitME.pdf |refitME.html
refitME/json (API)

# Install 'refitME' in R:
install.packages('refitME', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 9 scripts 112 downloads 8 exports 83 dependencies

Last updated 3 years agofrom:0e3631b55c. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 23 2024
R-4.5-linuxNOTEOct 23 2024

Exports:anova_MCEMfit_glmlogLik_MCEMfit_lmMCEMfit_CRMCEMfit_gamMCEMfit_genMCEMfit_glmrefitMEwt.var

Dependencies:caretclasscliclockclustercodetoolscolorspacecpp11data.tablediagramdigestdplyre1071expmfansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellmvtnormnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartsandwichscalesSemiParshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsVGAMVGAMdataviridisLitewithrzoo