Package: lavacreg 0.2-2

Christoph Kiefer

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>.

Authors:Christoph Kiefer [cre, aut]

lavacreg_0.2-2.tar.gz
lavacreg_0.2-2.tar.gz(r-4.7-arm64)lavacreg_0.2-2.tar.gz(r-4.7-x86_64)lavacreg_0.2-2.tar.gz(r-4.6-arm64)lavacreg_0.2-2.tar.gz(r-4.6-x86_64)
lavacreg_0.2-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
lavacreg/json (API)
NEWS

# Install 'lavacreg' in R:
install.packages('lavacreg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/chkiefer/lavacreg/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • example01 - A first example dataset to illustrate the use of lavacreg

On CRAN:

Conda:

openblascppopenmp

2.70 score 6 scripts 664 downloads 3 exports 5 dependencies

Last updated from:5f816fe39e. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK151
linux-devel-x86_64OK137
source / vignettesOK205
linux-release-arm64OK137
linux-release-x86_64OK137
wasm-releaseOK124

Exports:countregis_countsummary

Dependencies:fastGHQuadpracmaRcppRcppArmadilloSparseGrid

Introduction

Rendered fromintro.Rmdusingknitr::rmarkdownon Jun 11 2026.

Last update: 2023-10-23
Started: 2021-02-16