The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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 |
Reference manual: | lavacreg.pdf |
Vignettes: |
Introduction |
Package source: | lavacreg_0.2-2.tar.gz |
Windows binaries: | r-devel: lavacreg_0.2-2.zip, r-release: lavacreg_0.2-2.zip, r-oldrel: lavacreg_0.2-2.zip |
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 |
Please use the canonical form https://CRAN.R-project.org/package=lavacreg to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.