lavacreg: Latent Variable Count Regression Models (original) (raw)
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  [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 |
| Materials: | README NEWS |
| CRAN checks: | lavacreg results |
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