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: 0.2-2
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.5), fastGHQuad, pracma, methods, stats, SparseGrid
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat
Published: 2024-06-13
DOI: 10.32614/CRAN.package.lavacreg
Author: Christoph Kiefer ORCID iD [cre, aut]
Maintainer: Christoph Kiefer <christoph.kiefer at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: lavacreg results


Reference manual: lavacreg.pdf
Vignettes: Introduction


Package source: lavacreg_0.2-2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): lavacreg_0.2-2.tgz, r-oldrel (arm64): lavacreg_0.2-2.tgz, r-release (x86_64): lavacreg_0.2-2.tgz, r-oldrel (x86_64): lavacreg_0.2-2.tgz
Old sources: lavacreg archive


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