Sparse composite likelihood selection [PDF]
, 2021 Composite likelihood has shown promise in settings where the number of parameters $p$ is large due to its ability to break down complex models into simpler components, thus enabling inference even when the full likelihood is not tractable. Although there are a number of ways to formulate a valid composite likelihood in the finite-$p$ setting, there ...
C. Di Caterina, D. Ferrari
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Penalized Composite Likelihood Estimation for Spatial Generalized Linear Mixed Models [PDF]
Journal of Sciences, Islamic Republic of IranWhen discussing non-Gaussian spatially correlated variables, generalized linear mixed models have enough flexibility for modeling various data types. However, the maximum likelihood methods are plagued with substantial calculations for large data sets ...
Mohsen Mohammadzadeh, Leyla Salehi
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Pairwise likelihood estimation for multivariate mixed Poisson models generated by Gamma intensities [PDF]
, 2009 Estimating the parameters of multivariate mixed Poisson models is an important problem in image processing applications, especially for active imaging or astronomy.
Jean-Yves Tourneret +5 more
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Independent distinctive role of the earlier sign in the composite sign and likelihood of confusion in trade [PDF]
Glasnik Advokatske komore Vojvodine, 2017 In this paper, the author analyzes the factor of the independent distinctive role of the earlier sign in the composite sign from different points of view.
Volarević Ninoslav
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Adjusted composite likelihood ration test for spatial Gibbs point processes [PDF]
, 2015 © 2015 Taylor & Francis We investigate an analogue of the likelihood ratio test for spatial Gibbs point process models fitted by maximum pseudolikelihood or maximum composite likelihood.
Rubak, E. +7 more
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Efficiency Bound of Local Z-Estimators on Discrete Sample Spaces
Entropy, 2016 Many statistical models over a discrete sample space often face the computational difficulty of the normalization constant. Because of that, the maximum likelihood estimator does not work.
Takafumi Kanamori
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Empirical likelihood confidence intervals for complex sampling designs [PDF]
, 2016 We define an empirical likelihood approach which gives consistent design-based confidence intervals which can be calculated without the need of variance estimates, design effects, resampling, joint inclusion probabilities and linearization, even when the
De La Riva Torres, O., Berger, Y.G.
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Detecting Recombination Hotspots from Patterns of Linkage Disequilibrium
G3: Genes, Genomes, Genetics, 2016 With recent advances in DNA sequencing technologies, it has become increasingly easy to use whole-genome sequencing of unrelated individuals to assay patterns of linkage disequilibrium (LD) across the genome.
Jeffrey D. Wall, Laurie S. Stevison
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Estimation in the presence of many nuisance parameters: Composite likelihood and plug-in likelihood
Stochastic Processes and their Applications, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Billy Wu, Qiwei Yao, Shiwu Zhu
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Sparse composite likelihood selection [PDF]
, 2022 Composite likelihood has shown promise in settings with large num- ber of parameters p due to its ability to break down complex models into simpler components, even when the full likelihood is intractable.
C. Di Caterina, D. Ferrari
core