Poisson mean vector estimation with nonparametric maximum likelihood estimation and application to protein domain data

DOI10.1214/22-EJS2029zbMath1493.62176OpenAlexW4285196810MaRDI QIDQ2161181

Junyong Park, Hoyoung Park

Publication date: 4 August 2022

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/journals/electronic-journal-of-statistics/volume-16/issue-2/Poisson-mean-vector-estimation-with-nonparametric-maximum-likelihood-estimation-and/10.1214/22-EJS2029.full

zbMATH Keywords

empirical BayesPoisson distributioncompound decision problemnonparametric maximum likelihood estimate

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Empirical decision procedures; empirical Bayes procedures (62C12) Compound decision problems in statistical decision theory (62C25)

Uses Software

• DEseq
• REBayes

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Two modeling strategies for empirical Bayes estimation
• Asymptotic theory for maximum likelihood in nonparametric mixture models
• Robbins, empirical Bayes and microarrays
• Compound decision theory and empirical Bayes methods
• Approximate nonparametric maximum likelihood for mixture models: a convex optimization approach to fitting arbitrary multivariate mixing distributions
• Probability inequalities for likelihood ratios and convergence rates of sieve MLEs
• Weak convergence and empirical processes. With applications to statistics
• On general maximum likelihood empirical Bayes estimation of heteroscedastic IID normal means
• On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising
• General maximum likelihood empirical Bayes estimation of normal means
• Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means
• High-dimensional classification via nonparametric empirical Bayes and maximum likelihood inference
• Nonparametric empirical Bayes estimator in simultaneous estimation of Poisson means with application to mass spectrometry data
• Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data
• Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
• A note on Poisson maxima
• Simultaneous Poisson Estimators for a Priori Hypotheses about Means
• Simultaneous Estimation of the Means of Independent Poisson Laws
• Prediction and estimation for the compound Poisson distribution
• SURE Estimates for a Heteroscedastic Hierarchical Model
• Group-Linear Empirical Bayes Estimates for a Heteroscedastic Normal Mean
• Convex Optimization, Shape Constraints, Compound Decisions, and Empirical Bayes Rules
• The Poisson Compound Decision Problem Revisited
• Empirical Bayes estimation for the Poisson distribution
• Generalized likelihood ratio test for normal mixtures

This page was built for publication: Poisson mean vector estimation with nonparametric maximum likelihood estimation and application to protein domain data