Package: lavacreg
Type: Package
Title: Latent Variable Count Regression Models
Version: 0.1-2
Date: 2021-08-19
Authors@R: c(person("Christoph", "Kiefer", 
                    email = "christoph.kiefer@uni-bielefeld.de", 
                    role = c("cre", "aut"), 
                    comment = c(ORCID = "0000-0002-9166-400X"))) 
Description: 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>.
License: GPL (>= 2)
URL: https://github.com/chkiefer/lavacreg
BugReports: https://github.com/chkiefer/lavacreg/issues
LazyData: true
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.5), fastGHQuad, pracma, methods, stats,
        SparseGrid
LinkingTo: Rcpp
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2021-08-19 14:51:06 UTC; christoph
Author: Christoph Kiefer [cre, aut] (<https://orcid.org/0000-0002-9166-400X>)
Maintainer: Christoph Kiefer <christoph.kiefer@uni-bielefeld.de>
Repository: CRAN
Date/Publication: 2021-08-19 17:20:02 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 15:15:37 UTC; windows
Archs: i386, x64
