Asymptotic properties of predictive recursion: robustness and rate of convergence

DOI10.1214/09-EJS458zbMath1326.62107OpenAlexW2122454068MaRDI QIDQ1952032

Ryan Martin, Surya T. Tokdar

Publication date: 27 May 2013

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

Full work available at URL: https://projecteuclid.org/euclid.ejs/1261671305

zbMATH Keywords

empirical Bayesdensity estimationmixture modelsKullback-Leibler projectionalmost supermartingale

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Nonparametric estimation (62G05)

Related Items (13)

Convergence of an iterative algorithm to the nonparametric MLE of a mixing distribution ⋮ On Recursive Bayesian Predictive Distributions ⋮ A semiparametric scale-mixture regression model and predictive recursion maximum likelihood ⋮ Convergence rate for predictive recursion estimation of finite mixtures ⋮ Revisiting consistency of a recursive estimator of mixing distributions ⋮ A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions ⋮ A class of measure-valued Markov chains and Bayesian nonparametrics ⋮ A Laplace transform inversion method for probability distribution functions ⋮ An Approximate Bayesian Marginal Likelihood Approach for Estimating Finite Mixtures ⋮ A survey of nonparametric mixing density estimation via the predictive recursion algorithm ⋮ On an algorithm for solving Fredholm integrals of the first kind ⋮ Asymptotically Optimal Nonparametric Empirical Bayes Via Predictive Recursion ⋮ Estimating a mixing distribution on the sphere using predictive recursion

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