GJRM: Generalised Joint Regression Modelling

Routines for fitting various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations' errors association, endogeneity, non-random sample selection or partial observability.

Version: 0.2-5
Depends: R (≥ 3.2.1), mgcv
Imports: magic, matrixcalc, VGAM, survey, trust, VineCopula, graphics, stats, utils, grDevices, ggplot2, matrixStats, mnormt, gamlss.dist, Rmpfr, scam, survival, psych, copula, distrEx, numDeriv, trustOptim, evd, ismev
Enhances: sp
Published: 2021-09-17
Author: Giampiero Marra and Rosalba Radice
Maintainer: Giampiero Marra <giampiero.marra at ucl.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.ucl.ac.uk/statistics/people/giampieromarra
NeedsCompilation: no
Citation: GJRM citation info
Materials: ChangeLog
CRAN checks: GJRM results

Downloads:

Reference manual: GJRM.pdf
Package source: GJRM_0.2-5.tar.gz
Windows binaries: r-devel: GJRM_0.2-4.zip, r-release: GJRM_0.2-4.zip, r-oldrel: GJRM_0.2-4.zip
macOS binaries: r-release (arm64): GJRM_0.2-4.tgz, r-release (x86_64): GJRM_0.2-4.tgz, r-oldrel: GJRM_0.2-4.tgz
Old sources: GJRM archive

Reverse dependencies:

Reverse imports: miceMNAR, penfa

Linking:

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