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-4.5-noble)lavacreg_0.2-2.tar.gz(r-4.4-noble)
lavacreg_0.2-2.tgz(r-4.4-emscripten)lavacreg_0.2-2.tgz(r-4.3-emscripten)
lavacreg.pdf |lavacreg.html
lavacreg/json (API)
NEWS

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

Peer review:

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

openblascppopenmp

2.70 score 5 scripts 589 downloads 3 exports 5 dependencies

Last updated 6 months agofrom:5f816fe39e. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 03 2024
R-4.5-linux-x86_64OKDec 03 2024

Exports:countregis_countsummary

Dependencies:fastGHQuadpracmaRcppRcppArmadilloSparseGrid

Introduction

Rendered fromintro.Rmdusingknitr::rmarkdownon Dec 03 2024.

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