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ebTobit
View on CRAN: Click
here
Download and install ebTobit package within the R console
Install from CRAN:
install.packages("ebTobit")
Install from Github:
library("remotes")
install_github("cran/ebTobit") Install by package version:
library("remotes")
install_version("ebTobit", "1.0.2") Attach the package and use:
library("ebTobit")
Maintained by
Alton Barbehenn
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-15
Latest Update: 2024-05-03
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) . Additional, lower-level functionality based
on Kiefer and Wolfowitz (1956) and Jiang and
Zhang (2009) is provided that can be used to
accelerate many empirical Bayes and nonparametric maximum likelihood
problems.
How to cite:
Alton Barbehenn (2023). ebTobit: Empirical Bayesian Tobit Matrix Estimation. R package version 1.0.2, https://cran.r-project.org/web/packages/ebTobit. Accessed 06 Mar. 2026.
Previous versions and publish date:
1.0.1 (2023-06-15 09:30)
Other packages that cited ebTobit R package
View ebTobit citation profile
Other R packages that ebTobit depends,
imports, suggests or enhances
Complete documentation for ebTobit
Functions, R codes and Examples using
the ebTobit R package
Some associated functions: BileAcid . ConvexDual . ConvexPrimal . EM . ebTobit . fitted.ebTobit . is.ebTobit . likMat . lik_GaussianPIC . logLik.ebTobit . new_ebTobit . posterior_L1mediod.ebTobit . posterior_mean.ebTobit . posterior_mode.ebTobit . predict.ebTobit . tobit_sd . tobit_sd_mle .
Some associated R codes: BileAcid.R . RcppExports.R . S3utils.R . ebTobit.R . fittingMethods.R . tobit_sd.R . Full ebTobit package functions and examples
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