On composite marginal likelihoods

By Cristiano Varin. 2008

366 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/595c86bf6cb4ee56c20012dbf72d02d4ba7982f6

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In Artificial Intelligence

In Statistics and Probability

Citations in the corpus

Bayesian composite marginal likelihoods (2011, methodology): “Their use has been widely advocated by several authors in different complex applications of frequentist inference (see Varin (2008), and Varin, Reid and Firth (2009) for recent reviews).”
On the robustness of maximum composite likelihood estimate (2011, neutral): “This section and the next is a complement to the discussions on the robustness of composite likelihood inference in Varin (2008) and Varin et al. (2011).”
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison (2014, methodology): “A way to overcome the limitations of EM is by considering relaxed versions of the maximum likelihood principle (Varin, 2008).”
The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models (2011, background): “7 A handful of studies (see Hjort and Varin, 2008; Mardia et al., 2009; Cox and Reid, 2004) have also theoretically examined the limiting normality properties of the CML approach, and compared the asymptotic variance matrices from this approach and the ML approach.”
Maximum likelihood estimation using composite likelihoods for closed exponential families (2009, background): “Varin (2008) is a recent review paper with a wealth of examples.”
Minimum Scoring Rule Inference (2014, background): “A consistent estimate of V can be obtained using estimates of the matrices J and K: Ĵ = n∑ i=1 s(xi, θ̂S)s(xi, θ̂S) T K̂ = n∑ i=1 ∂s(xi, θ)/∂θ T ∣∣ θ=θ̂S ; one can refer to Varin (2008) and Varin et al. (2011) for a detailed discussion of the issues related to the estimation of J and K.”
Copula-based geostatistical modeling of continuous and discrete data including covariates (2010, background): “Their applications to spatial data are studied by Varin (2008) .”
ADJUSTING COMPOSITE LIKELIHOOD RATIO STATISTICS (2009, methodology): “Matching of moments up to higher order can also be considered, as in Wood (1989). See also Lindsay, Pilla, and Basak (2000).”
Statistical Modelling of Spatial Extremes (2012, methodology): “Composite likelihood is increasingly used in problems where the full likelihood is unobtainable or too burdensome for ready computation, and there is a burgeoning literature on the topic, summarised by Varin (2008).”
Econometric Analysis of Vast Covariance Matrices Using Composite Realized Kernels and Their Application to Portfolio Choice (2016, background): “See Varin (2008) and Varin, Reid, and Firth (2011) for a modern review.”
Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes (2009, background): “Varin (2008) proposes a Satterthwaite adjustment to match the first two moments of Λmagn(ψ0) and χ 2 q , though their higher moments would still differ.”
Spatial modeling of extreme snow depth (2011, background): “Padoan, Ribatet and Sisson (2010) proposed replacing the full likelihood by a pairwise likelihood function [Cox and Reid (2004); Varin (2008)].”
AN OVERVIEW OF COMPOSITE LIKELIHOOD METHODS (2011, methodology): “For further discussion of this approach see Varin (2008).”