A note on Monte Carlo maximization by the density ratio model

DOI10.1080/15598608.2008.10411880zbMath1211.62057OpenAlexW2018703907MaRDI QIDQ715773

Jing Qin, Konstantinos Fokianos

Publication date: 18 April 2011

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15598608.2008.10411880

zbMATH Keywords

likelihood ratioempirical likelihoodnormalizing constantbiased samplingdensity ratio model

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Monte Carlo methods (65C05)

Related Items (3)

Bayesian semiparametric density ratio modelling with applications to medical malpractice reform ⋮ Estimation of tail probabilities by repeated augmented reality ⋮ Out-of-sample fusion in risk prediction

Cites Work

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• Empirical likelihood and general estimating equations
• Large sample theory of maximum likelihood estimates in semiparametric biased sampling models.
• Empirical likelihood ratio confidence intervals for a single functional
• Logistic disease incidence models and case-control studies
• Some results on the estimation of logistic models based on retrospective data
• Multivariate logistic compounds
• Inferences for case-control and semiparametric two-sample density ratio models
• Maximum likelihood estimation in semiparametric selection bias models with application to AIDS vaccine trials
• A goodness-of-fit test for logistic regression models based on case-control data
• A Semiparametric Approach to the One-Way Layout
• A Theory of Statistical Models for Monte Carlo Integration
• Separate sample logistic discrimination
• Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.

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