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Marginal likelihood, conditional likelihood and empirical likelihood: Connections and applications
Biometrika, 2005Marginal likelihood and conditional likelihood are often used for eliminating nuisance parameters. For a parametric model, it is well known that the full likelihood can be decomposed into the product of a conditional likelihood and a marginal likelihood. This property is less transparent in a nonparametric or semiparametric likelihood setting.
Jing Qin, Biao Zhang
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Self‐concordance for empirical likelihood
Canadian Journal of Statistics, 2013AbstractAbstractThe usual approach to computing empirical likelihood for the mean uses Newton's method after eliminating a Lagrange multiplier and replacing the function by a quadratic Taylor approximation to the left of . This paper replaces the quadratic approximation by a quartic.
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Bayesian Empirical Likelihood Methods
2020In this chapter, we first provide a brief review of Bayesian approaches to finite population inference. We then present Bayesian empirical likelihood methods for the finite population mean as well as general parameters defined through estimating functions.
Changbao Wu, Mary E. Thompson
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Empirical Likelihood Block Bootstrapping
2008Monte Carlo evidence has made it clear that asymptotic tests based on generalized method of moments (GMM) estimation have disappointing size. The problem is exacerbated when the moment conditions are serially correlated. Several block bootstrap techniques have been proposed to correct the problem, including Hall and Horowitz (1996) and Inoue and ...
Allen, Jason +5 more
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Empirical likelihood ratio confidence intervals for a single functional
, 1988A. Owen
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Connections Among Marginal Likelihood, Conditional Likelihood and Empirical Likelihood
2017In this Chapter we present the results by Qin and Zhang (Biometrika 92:251–270, 2005) and Li and Qin (JASA 496:1476–1484, 2011) on the connection between marginal likelihood, conditional likelihood and empirical likelihood.
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Portfolio Analysis Using Stochastic Dominance, Relative Entropy, and Empirical Likelihood
Management Sciences, 2017T. Post, Valerio Potì
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Transforming the empirical likelihood towards better accuracy
, 2017Bing-Yi Jing, Min Tsao, Wang Zhou
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