Package: HZIP
Type: Package
Title: Likelihood-Based Inference for Joint Modeling of Correlated
        Count and Binary Outcomes with Extra Variability and Zeros
Version: 0.1.2
Authors@R: c(person("Lizandra C.", "Fabio", email = "lizandra.fabio@ufba.br", role = "aut"),
  person("Jalmar M. F.", "Carrasco", email = "carrasco.jalmar@ufba.br", role = c("aut", "cre")),
  person("Victor H.", "Lachos", email = "hlachos@uconn.edu", role = "aut"),
  person("Ming-Hui", "Chen", email = "ming-hui.chen@uconn.edu", role = "aut"))
Author: Lizandra C. Fabio [aut],
  Jalmar M. F. Carrasco [aut, cre],
  Victor H. Lachos [aut],
  Ming-Hui Chen [aut]
Maintainer: Jalmar M. F. Carrasco <carrasco.jalmar@ufba.br>
Description: Inference approach for jointly modeling correlated count and binary outcomes. This formulation allows simultaneous modeling of zero inflation via the Bernoulli component while providing a more accurate assessment of the Hierarchical Zero-Inflated Poisson's parsimony (Lizandra C. Fabio, Jalmar M. F. Carrasco, Victor H. Lachos and Ming-Hui Chen, Likelihood-based inference for joint modeling of correlated count and binary outcomes with extra variability and zeros, 2026, under submission).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
LinkingTo: Rcpp, RcppParallel, RcppArmadillo
Imports: Rcpp, Formula, pscl, stats, tibble, dplyr, statmod,
        RcppParallel, ggplot2, numDeriv, rlang
Depends: R (>= 3.5)
URL: https://github.com/carrascojalmar/HZIP
BugReports: https://github.com/carrascojalmar/HZIP/issues
NeedsCompilation: yes
Packaged: 2026-06-02 19:55:43 UTC; jalmarcarrasco
Repository: CRAN
Date/Publication: 2026-06-02 20:20:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-06-02 21:27:59 UTC; unix
Archs: HZIP.so.dSYM
