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 
[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 |
Documentation:
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