mult.latent.reg: Regression and Clustering in Multivariate Response Scenarios

Fitting multivariate response models with random effects on one or two levels; whereby the (one-dimensional) random effect represents a latent variable approximating the multivariate space of outcomes, after possible adjustment for covariates. The method is particularly useful for multivariate, highly correlated outcome variables with unobserved heterogeneities. Applications include regression with multivariate responses, as well as multivariate clustering or ranking problems. See Zhang and Einbeck (2024) <doi:10.1007/s42519-023-00357-0>.

Version:	0.2.1
Depends:	R (≥ 3.5.0)
Imports:	mvtnorm, stats, matrixStats, utils, lme4
Published:	2024-11-15
DOI:	10.32614/CRAN.package.mult.latent.reg
Author:	Yingjuan Zhang [aut, cre], Jochen Einbeck [aut, ctb]
Maintainer:	Yingjuan Zhang <yingjuan.zhang at durham.ac.uk>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	mult.latent.reg results

Documentation:

Reference manual:

mult.latent.reg.pdf

Downloads:

Package source:	mult.latent.reg_0.2.1.tar.gz
Windows binaries:	r-devel: mult.latent.reg_0.2.1.zip, r-release: mult.latent.reg_0.2.1.zip, r-oldrel: mult.latent.reg_0.2.1.zip
macOS binaries:	r-release (arm64): mult.latent.reg_0.2.1.tgz, r-oldrel (arm64): mult.latent.reg_0.2.1.tgz, r-release (x86_64): mult.latent.reg_0.2.1.tgz, r-oldrel (x86_64): mult.latent.reg_0.2.1.tgz
Old sources:	mult.latent.reg archive

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