Empirical Bayes Estimation of Treatment Effects with Many A/B Tests: An Overview

Empirical Bayes Estimation in Nonstationary Markov chains

Estimation procedures for nonstationary Markov chains appear to be relatively sparse. This work introduces empirical  Bayes estimators  for the transition probability  matrix of a finite nonstationary  Markov chain. The data are assumed to be of  a panel study type in which each data set consists of a sequence of observations on N>=2 independent and identically dis...

Empirical Bayes Tests Based on Kernel Sequence Estimation

In this paper, we consider the hypothesis-testing problem in the continuous one-parameter exponential family using the nonparametric empirical Bayes approach. In order to estimate an unknown marginal density and its derivative, a kernel sequence method is introduced. This method uses a sequence of kernel functions and allows the kernel index and window bandwidth to vary simultaneously. Thus imp...

Empirical Bayes Estimation of Reliability

Assessment of the reliability of various types of equipment relies on statistical inference about characteristics of reliability such as reliability function, mean lifetime of the devices, or failure rate. General techniques of statistical inference (estimation and hypotheses testing) are reviewed in Estimation; Least-Squares Estimation; Maximum Likelihood; Nonparametric Tests; Hypothesis Testi...

Empirical Bayes Regression Analysis with Many Regressors but Fewer Observations

In this paper, we consider the prediction problem in multiple linear regression model in which the number of predictor variables, p, is extremely large compared to the number of available observations, n. The least squares predictor based on a generalized inverse is not efficient. We propose six empirical Bayes estimators of the regression parameters. Three of them are shown to have uniformly l...

Supplement to Empirical Bayes Regression with Many Regressors