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Data from: Predictive Bayesian selection of multistep Markov chains, applied to the detection of the hot hand and other statistical dependencies
负责人:
关键词:
Markov chain;selection;Bayesian;Hot hand
DOI:
doi:10.5061/dryad.4k25m2q
摘要:
n) does not clearly beat a model with independent outcomes. An error-correcting variable length model of two parameters, where James shoots a higher
Data from: Across population genomic prediction scenarios in which Bayesian variable selection outperforms GBLUP
负责人:
关键词:
Genomic prediction across population Bayesian variable selection GBLUP accuracy number of independent chromosome segments
DOI:
doi:10.5061/dryad.rq80k
摘要:
rrently disappointing. It has been shown for within population genomic prediction that Bayesian variable selection models outperform GBLUP models
Data from: Bayesian inference of selection in a heterogeneous environment from genetic time-series data
负责人:
关键词:
Natural Selection and Contemporary Evolution;Ecological Genetics;Adaptation;Population Genetics - Empirical
DOI:
doi:10.5061/dryad.14853
摘要:
on in populations. Herein, I proposed a Bayesian non-homogenous hidden Markov model to estimate effective population sizes and quantify variable selection
Data from: A hidden Markov model to identify and adjust for selection bias: an example involving mixed migration strategies
负责人:
关键词:
winter severity;Bayesian;white-tailed deer;Migration;state-space;partially observed state;latent variable;1991-2006;Odocoileus virginianus
DOI:
doi:10.5061/dryad.4430n
摘要:
ck-to-back severe winters. These results support the hypothesis that selection biases occur as a result of capturing deer on winter yards, with the magnitude
Data from: Genomic evidence that resource-based trade-offs limit host-range expansion in a seed beetle
负责人:
关键词:
population genetics;Selection - Experimental;Plant-Insect Interaction;Adaptation
DOI:
doi:10.5061/dryad.1p0rm
摘要:
on. Bayesian estimates of selection coefficients suggest that rapid adaptation to a poor host (lentil) was mediated by standing genetic variati
Data from: Demographic history and adaptation account for clock gene diversity in humans
负责人:
关键词:
environment;natural selection;population structure;Adaptation;Clock genes
DOI:
doi:10.5061/dryad.pr078
摘要:
or sleep disorders. Correlation of five such SNPs with environmental variables supports a selective role of latitude or photoperiod, but certainly not a major one.
Data from: Historical connectivity, contemporary isolation, and local adaptation in a widespread but discontinuously distributed species
负责人:
关键词:
plant-climate interactions;Dispersal;adaptive divergence;Rhododendron oldhamii;habitat fragmentation
DOI:
doi:10.5061/dryad.nc221
摘要:
ks, and historical and contemporary gene flow. Selection associated with environmental variables was also examined. Bayesian clustering analysis revealed four regional
Data from: Variable hybridization outcomes in trout are predicted by historical fish stocking and environmental context
负责人:
关键词:
Oncorhynchus clarkii bouvieri;Fish;hybridization;Oncorhynchus mykiss;speciation;Population Genetics - Empirical
DOI:
doi:10.5061/dryad.6s7d02q
摘要:
ons of random mating and no selection against hybrids. Since this implies that some mechanisms of reproductive isolation function to maintain parental taxa
Data from: Genetic subdivision and candidate genes under selection in North American gray wolves
负责人:
关键词:
Genomics\/Proteomics;Mammals;Holocene;Canis lupus;Ecological Genetics;Adaptation;Population Genetics - Empirical
DOI:
doi:10.5061/dryad.c9b25
摘要:
ecotypes through the use of three complementary methods to detect selection: FST/haplotype homozygosity bivariate percentile, BayeScan, and environmentally
Data from: How characteristic is the species characteristic selection scale?
负责人:
关键词:
Multi-scale;N-mixture;SCSS;Bayesian latent indicator scale selection;BLISS;hierarchical model;spatial scale;species-environment relationship;species-habitat
DOI:
doi:10.5061/dryad.31ks8p5
摘要:
hierarchical N-mixture models relating species abundance to landcover variables. By incorporating Bayesian latent indicator scale selection, we identi

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