On constructing sequences estimating the mixing distribution with applications

DOI10.1080/03610919008812883zbMath0731.62085OpenAlexW1992154621MaRDI QIDQ3357347

Robert F. Phillips

Publication date: 1990

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610919008812883

zbMATH Keywords

mixturelinear programmingweak convergencesimulationmixing distributiondensity estimatesChebyshev normsupremum normnonparametric empirical Bayes estimates

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Applications of mathematical programming (90C90) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (1)

Minimum Hellinger distance estimation for Poisson mixtures.

Cites Work

• The geometry of mixture likelihoods, part II: The exponential family
• The geometry of mixture likelihoods: A general theory
• Some thoughts on empirical Bayes estimation
• Mixtures of exponential distributions
• Estimation of a mixing distribution function
• Statistical analysis of finite mixture distributions
• Empirical bayes estimates using the nonparametric maximum likelihood estimate for the priort
• Nonparametric Maximum Likelihood Estimation of a Mixing Distribution
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
• The Empirical Bayes Approach to Statistical Decision Problems
• Construction of Sequences Estimating the Mixing Distribution

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