ebTobit: Empirical Bayesian Tobit Matrix Estimation

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.

Version:	1.0.2
Depends:	R (≥ 3.3.0)
Imports:	Rcpp (≥ 1.0.10), RcppParallel, stats
LinkingTo:	Rcpp, RcppArmadillo, RcppParallel
Suggests:	REBayes
Published:	2024-05-03
DOI:	10.32614/CRAN.package.ebTobit
Author:	Alton Barbehenn [aut, cre], Sihai Dave Zhao [aut]
Maintainer:	Alton Barbehenn <altonbarbehenn at gmail.com>
BugReports:	https://github.com/barbehenna/ebTobit/issues
License:	GPL-3
URL:	https://github.com/barbehenna/ebTobit
NeedsCompilation:	yes
Materials:	README
CRAN checks:	ebTobit results

Documentation:

Reference manual:

ebTobit.pdf

Downloads:

Package source:	ebTobit_1.0.2.tar.gz
Windows binaries:	r-devel: ebTobit_1.0.2.zip, r-release: ebTobit_1.0.2.zip, r-oldrel: ebTobit_1.0.2.zip
macOS binaries:	r-release (arm64): ebTobit_1.0.2.tgz, r-oldrel (arm64): ebTobit_1.0.2.tgz, r-release (x86_64): ebTobit_1.0.2.tgz, r-oldrel (x86_64): ebTobit_1.0.2.tgz
Old sources:	ebTobit archive

Linking:

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