lavacreg: Latent Variable Count Regression Models

Estimation of a multi-group count regression models (i.e., Poisson, negative binomial) with latent covariates. This packages provides two extensions compared to ordinary count regression models based on a generalized linear model: First, measurement models for the predictors can be specified allowing to account for measurement error. Second, the count regression can be simultaneously estimated in multiple groups with stochastic group weights. The marginal maximum likelihood estimation is described in Kiefer & Mayer (2020) <doi:10.1080/00273171.2020.1751027>.

Version: 0.1-0
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.5), fastGHQuad, pracma, methods, stats
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat
Published: 2021-02-16
Author: Christoph Kiefer ORCID iD [cre, aut]
Maintainer: Christoph Kiefer <christoph.kiefer at uni-bielefeld.de>
BugReports: https://github.com/chkiefer/lavacreg/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/chkiefer/lavacreg
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README NEWS
CRAN checks: lavacreg results

Downloads:

Reference manual: lavacreg.pdf
Vignettes: Introduction
Package source: lavacreg_0.1-0.tar.gz
Windows binaries: r-devel: lavacreg_0.1-0.zip, r-release: not available, r-oldrel: not available
macOS binaries: r-release: not available, r-oldrel: not available

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