Maximum Composite Likelihood Estimation for Spatial Extremes Models of Brown‐Resnick type with Application to Precipitation Data

2021 ◽  
Author(s):  
Moosup Kim ◽  
Sangyeol Lee
Keyword(s):  
Likelihood Estimation ◽  
Composite Likelihood ◽  
Precipitation Data ◽  
Spatial Extremes ◽  
Maximum Composite Likelihood

scholarly journals Effective population size and tests of neutrality at cytoplasmic genes in Arabidopsis

2008 ◽  
Vol 90 (1) ◽  
pp. 119-128 ◽  
Author(s):  
STEPHEN I. WRIGHT ◽  
NARDIN NANO ◽  
JOHN PAUL FOXE ◽  
VAQAAR-UN NISA DAR
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Likelihood Estimation ◽  
Composite Likelihood ◽  
Nuclear Genes ◽  
Nucleotide Polymorphism ◽  
Effective Population ◽  
Arabidopsis Lyrata ◽  
Tests Of Neutrality ◽  
Low Levels

SummaryCytoplasmic genomes typically lack recombination, implying that genetic hitch-hiking could be a predominant force structuring nucleotide polymorphism in the chloroplast and mitochondria. We test this hypothesis by analysing nucleotide polymorphism data at 28 loci across the chloroplast and mitochondria of the outcrossing plant Arabidopsis lyrata, and compare patterns with multiple nuclear loci, and the highly selfing Arabidopsis thaliana. The maximum likelihood estimate of the ratio of effective population size at cytoplasmic relative to nuclear genes in A. lyrata does not depart from the neutral expectation of 0·5. Similarly, the ratio of effective size in A. thaliana is close to unity, the neutral expectation for a highly selfing species. The results are thus consistent with neutral organelle polymorphism in these species or with comparable effects of hitch-hiking in both cytoplasmic and nuclear genes, in contrast to the results of recent studies on gynodioecious taxa. The four-gamete test and composite likelihood estimation provide evidence for very low levels of recombination in the organelles of A. lyrata, although permutation tests do not suggest that adjacent polymorphic sites are more closely linked than more distant sites across the two genomes, suggesting that mutation hotspots or very low rates of gene conversion could explain the data.

scholarly journals Multiple Comparisons Using Composite Likelihood in Clustered Data

2016 ◽  
Vol 12 (2) ◽  
Author(s):  
Mahdis Azadbakhsh ◽  
Xin Gao ◽  
Hanna Jankowski
Keyword(s):  
Type I Error ◽  
Clustered Data ◽  
Likelihood Estimation ◽  
Good Control ◽  
Multiple Hypothesis Testing ◽  
Composite Likelihood ◽  
Multiple Comparison ◽  
Likelihood Method ◽  
Type I ◽  
Multiple Comparison Procedures

AbstractWe study the problem of multiple hypothesis testing for correlated clustered data. As the existing multiple comparison procedures based on maximum likelihood estimation could be computationally intensive, we propose to construct multiple comparison procedures based on composite likelihood method. The new test statistics account for the correlation structure within the clusters and are computationally convenient to compute. Simulation studies show that the composite likelihood based procedures maintain good control of the familywise type I error rate in the presence of intra-cluster correlation, whereas ignoring the correlation leads to erratic performance.

scholarly journals Efficient pairwise composite likelihood estimation for spatial-clustered data

Biometrics ◽  
2014 ◽  
Vol 70 (3) ◽  
pp. 661-670 ◽  
Author(s):  
Yun Bai ◽  
Jian Kang ◽  
Peter X.-K. Song
Keyword(s):  
Clustered Data ◽  
Likelihood Estimation ◽  
Composite Likelihood

On composite likelihood estimation of a multivariate INAR(1) model

2012 ◽  
Vol 34 (2) ◽  
pp. 206-220 ◽  
Author(s):  
Xanthi Pedeli ◽  
Dimitris Karlis
Keyword(s):  
Likelihood Estimation ◽  
Composite Likelihood
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