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:	0.2-6
Depends:	R (≥ 3.2.1), mgcv
Imports:	magic, VGAM, survey, trust, VineCopula, graphics, stats, utils, grDevices, ggplot2, matrixStats, mnormt, gamlss.dist, Rmpfr, scam, survival, psych, copula, distrEx, numDeriv, evd, ismev
Enhances:	sp
Published:	2022-04-01
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
In views:	Survival
CRAN checks:	GJRM results

Documentation:

Reference manual:

GJRM.pdf

Downloads:

Package source:	GJRM_0.2-6.tar.gz
Windows binaries:	r-devel: GJRM_0.2-6.zip, r-release: GJRM_0.2-6.zip, r-oldrel: GJRM_0.2-6.zip
macOS binaries:	r-release (arm64): GJRM_0.2-6.tgz, r-oldrel (arm64): GJRM_0.2-6.tgz, r-release (x86_64): GJRM_0.2-6.tgz, r-oldrel (x86_64): GJRM_0.2-6.tgz
Old sources:	GJRM archive

Reverse dependencies:

Reverse imports:

penfa

Linking:

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