Results 251 to 260 of about 1,302,502 (286)

Empirical Likelihood Methods

2020
Publisher Summary Likelihood-based estimation methods in survey sampling do not follow as special cases from classical parametric likelihood inferences. The only randomization is induced by the probability sampling selection of units. While intervals based on NAs are clearly inappropriate, the EL interval maintains the same desirable performance ...
Changbao Wu, Mary E. Thompson
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EMPIRICAL LIKELIHOOD FOR GARCH MODELS

Econometric Theory, 2006
Summary: This paper develops an empirical likelihood approach for regular generalized autoregressive conditional heteroskedasticity (GARCH) models and GARCH models with unit roots. For regular GARCH models, it is shown that the log empirical likelihood ratio statistic asymptotically follows a \(\chi^2\) distribution.
Chan, NH, Ling, SQ
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Marginal likelihood, conditional likelihood and empirical likelihood: Connections and applications

Biometrika, 2005
Marginal 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, 2013
AbstractAbstractThe 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

2020
In 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

2008
Monte 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, Gregory, Allan W., Shimotsu, Katsumi, Allen, Jason, Gregory, Allan W., Shimotsu, Katsumi   +5 more
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Empirical Likelihood

Journal of the American Statistical Association, 2002
Zhao Y., Shen X.
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Connections Among Marginal Likelihood, Conditional Likelihood and Empirical Likelihood

2017
In 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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Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
exaly  

Empirical Likelihood

2018
Albert Vexler, Alan D. Hutson
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