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.

Getting started

Package details

AuthorAlton Barbehenn [aut, cre] (<https://orcid.org/0009-0000-3364-7204>), Sihai Dave Zhao [aut]
MaintainerAlton Barbehenn <altonbarbehenn@gmail.com>
LicenseGPL-3
Version1.0.2
URL https://github.com/barbehenna/ebTobit
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("ebTobit")

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ebTobit documentation built on May 29, 2024, 5:06 a.m.