Type: Package
Package: ebTobit
Title: Empirical Bayesian Tobit Matrix Estimation
Version: 1.0.2
Date: 2024-05-03
Authors@R: c(
    person("Alton", "Barbehenn", , "altonbarbehenn@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0009-0000-3364-7204")),
    person("Sihai Dave", "Zhao", , "sdzhao@illinois.edu", role = "aut")
  )
Description: Estimation tools for multidimensional Gaussian means using
    empirical Bayesian g-modeling. Methods are able to handle fully observed data as
    well as left-, right-, and interval-censored observations (Tobit
    likelihood); descriptions of these methods can be found in Barbehenn and
    Zhao (2023) <doi:10.48550/arXiv.2306.07239>. Additional, lower-level functionality based
    on Kiefer and Wolfowitz (1956) <doi:10.1214/aoms/1177728066> and Jiang and
    Zhang (2009) <doi:10.1214/08-AOS638> is provided that can be used to
    accelerate many empirical Bayes and nonparametric maximum likelihood
    problems.
License: GPL-3
URL: https://github.com/barbehenna/ebTobit
BugReports: https://github.com/barbehenna/ebTobit/issues
Imports: Rcpp (>= 1.0.10), RcppParallel, stats
Suggests: REBayes
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
Depends: R (>= 3.3.0)
NeedsCompilation: yes
Packaged: 2024-05-03 22:50:23 UTC; altonbarbehenn
Author: Alton Barbehenn [aut, cre] (<https://orcid.org/0009-0000-3364-7204>),
  Sihai Dave Zhao [aut]
Maintainer: Alton Barbehenn <altonbarbehenn@gmail.com>
Repository: CRAN
Date/Publication: 2024-05-03 23:00:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 18:30:25 UTC; unix
Archs: ebTobit.so.dSYM
