R: Empirical Bayesian Tobit Matrix Estimation

# Empirical Bayesian Tobit Matrix Estimation

## Documentation for package ‘ebTobit’ version 1.0.2

- DESCRIPTION file
- Package README

## Help Pages

BileAcid | Bile Acid Data
ConvexDual | Convex Optimization of the Kiefer-Wolfowitz NPMLE
ConvexPrimal | Convex Optimization of the Kiefer-Wolfowitz NPMLE
ebTobit | Empirical Bayes Matrix Estimation under a Tobit Likelihood
EM | Nonparametric Maximum Likelihood via Expectation Maximization
fitted.ebTobit | Fitted Estimates of an ebTobit object
is.ebTobit | Validate ebTobit Object
likMat | Helper Function - generate likelihood matrix
lik_GaussianPIC | Helper Function - generate likelihood for pair (L,R) and mean gr
logLik.ebTobit | Marginal Log-likelihood of an ebTobit object
new_ebTobit | Create a new ebTobit object
posterior_L1mediod.ebTobit | Compute the Posterior L1 Mediod of an ebTobit object
posterior_mean.ebTobit | Compute Posterior Mean of an ebTobit object
posterior_mode.ebTobit | Compute Posterior Mode of an ebTobit object
predict.ebTobit | Fitted Estimates of an ebTobit object
tobit_sd | Fit Tobit Standard Deviation via Maximum Likelihood
tobit_sd_mle | Maximum Likelihood Estimator for a Single Standard Deviation Parameter