Composite likelihood method for inferring local pedigrees. [PDF]
PLoS Genetics, 2017 Pedigrees contain information about the genealogical relationships among individuals and are of fundamental importance in many areas of genetic studies. However, pedigrees are often unknown and must be inferred from genetic data.
Amy Ko, Rasmus Nielsen
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Composite likelihood estimation of demographic parameters [PDF]
BMC Genetics, 2009 Background Most existing likelihood-based methods for fitting historical demographic models to DNA sequence polymorphism data to do not scale feasibly up to the level of whole-genome data sets. Computational economies can be achieved by incorporating two
Garrigan Daniel
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A topology-marginal composite likelihood via a generalized phylogenetic pruning algorithm [PDF]
Algorithms for Molecular Biology, 2023 Bayesian phylogenetics is a computationally challenging inferential problem. Classical methods are based on random-walk Markov chain Monte Carlo (MCMC), where random proposals are made on the tree parameter and the continuous parameters simultaneously ...
Seong-Hwan Jun +8 more
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On specification tests for composite likelihood inference. [PDF]
Biometrika, 2020 SummaryComposite likelihood functions are often used for inference in applications where the data have a complex structure. While inference based on the composite likelihood can be more robust than inference based on the full likelihood, the inference is not valid if the associated conditional or marginal models are misspecified.
Huang J, Ning Y, Reid N, Chen Y.
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Model Selection in a Composite Likelihood Framework Based on Density Power Divergence [PDF]
Entropy, 2020 This paper presents a model selection criterion in a composite likelihood framework based on density power divergence measures and in the composite minimum density power divergence estimators, which depends on an tuning parameter α .
Elena Castilla +3 more
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Accurate genetic and environmental covariance estimation with composite likelihood in genome-wide association studies. [PDF]
PLoS Genetics, 2021 Genetic and environmental covariances between pairs of complex traits are important quantitative measurements that characterize their shared genetic and environmental architectures.
Boran Gao, Can Yang, Jin Liu, Xiang Zhou
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Simulation based composite likelihood. [PDF]
Stat ComputAbstract Inference for high-dimensional hidden Markov models is challenging due to the exponential-in-dimension computational cost of calculating the likelihood. To address this issue, we introduce an innovative composite likelihood approach called “Simulation Based Composite Likelihood” (SimBa-CL).
Rimella L, Jewell C, Fearnhead P.
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Composite Likelihood Methods Based on Minimum Density Power Divergence Estimator [PDF]
Entropy, 2017 In this paper, a robust version of the Wald test statistic for composite likelihood is considered by using the composite minimum density power divergence estimator instead of the composite maximum likelihood estimator.
Elena Castilla +3 more
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Predicting protein inter-residue contacts using composite likelihood maximization and deep learning [PDF]
BMC Bioinformatics, 2019 Background Accurate prediction of inter-residue contacts of a protein is important to calculating its tertiary structure. Analysis of co-evolutionary events among residues has been proved effective in inferring inter-residue contacts.
Haicang Zhang +9 more
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Correction to: Predicting protein inter-residue contacts using composite likelihood maximization and deep learning [PDF]
BMC Bioinformatics, 2019 Following publication of the original article [1], the author explained that there are several errors in the original ...
Haicang Zhang +9 more
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