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Likelihood inference

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Abstract The essential role of the likelihood function in both Bayesian and non‐Bayesian inference is described. Several topics related to the extension of likelihood‐based methodology to more complex settings are reviewed, including modifications to profile likelihood, composite and pseudo‐likelihoods, quasi‐likelihood, semi‐parametric and non‐parametric likelihoods, and empirical likelihood. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Algorithms and Computational Methods > Maximum Likelihood Methods

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Algorithms and Computational Methods > Maximum Likelihood Methods

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