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Aspects of Composite Likelihood Inference [PDF]
, 2010 A composite likelihood consists of a combination of valid likelihood objects, and in particular it is of typical interest to adopt lower dimensional marginal likelihoods.
Jin, Zi
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Reliable inference for complex models by discriminative composite likelihood estimation [PDF]
, 2016 Composite likelihood estimation has an important role in the analysis of multivariate data for which the full likelihood function is intractable. An important issue in composite likelihood inference is the choice of the weights associated with lower ...
Zheng, Chao, Ferrari, Davide
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Adjusting composite likelihood ratio statistics [PDF]
, 2011 Composite likelihood may be useful for approximating likelihood based inference when the full likelihood is too complex to deal with. Stemming from a misspecified model, inference based on composite likelihood requires suitable corrections.
SALVAN, ALESSANDRA +2 more
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The Journal of Engineering, 2019 This paper proposes a probabilistic power pinch analysis (PoPA) approach based on Monte–Carlo simulation (MCS) for energy management of hybrid energy systems uncertainty.
Nyong-Bassey Bassey Etim +7 more
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Maximum likelihood estimation using composite likelihoods for closed exponential families [PDF]
Biometrika, 2009 In certain multivariate problems the full probability density has an awkward normalizing constant, but the conditional and/or marginal distributions may be much more tractable. In this paper we investigate the use of composite likelihoods instead of the full likelihood.
Kanti V. Mardia +3 more
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Using the Composite Likelihood Method on 4D AVA Seismic Data [PDF]
, 2011 This thesis is concerned with 4D AVA seismic inversion problems. By comparing two seismic surveys done over the same area, but at different times, one hopes to discover untapped pockets of oil or gas.
Borgan, Yngve
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Austrian Journal of Statistics, 2016 The Bayesian sequential test of composite hypotheses is considered. The situation of the simultaneously distorted prior probability distribution and likelihood is analyzed. The asymptotic expansions w.r.t.
Alexey Kharin
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Composite likelihood model selection [PDF]
, 2003 The Akaike information criterion has been derived under the assumptions that the model is “true”, or it is a good approximation to the truth, and that parameter estimation is obtained by using likelihood-based methods.
VARIN, CRISTIANO, VIDONI, PAOLO
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A General Bayesian Framework for Ellipse-based and Hyperbola-based Damage Localisation in Anisotropic Composite Plates [PDF]
, 2015 This paper focuses on Bayesian Lamb wave-based damage localization in structural health monitoring of anisotropic composite materials. A Bayesian framework is applied to take account for uncertainties from experimental time-of-flight measurements and ...
GUSKOV, Mikhail +3 more
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A Note on Information Bias and Efficiency of Composite Likelihood
Statistica SinicaDoes the asymptotic variance of the maximum composite likelihood estimator of a parameter of interest always decrease when the nuisance parameters are known? Will a composite likelihood necessarily become more efficient by incorporating addi- tional independent component likelihoods, or by using component likelihoods with higher dimension? In this note
Xu, Libai, Reid, Nancy, Xu, Ximing
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