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Data from: Bridging inter- and intraspecific trait evolution with a hierarchical Bayesian approach
- 负责人：
- DOI：
- doi:10.5061/dryad.n4vp0
- 摘要：
- s of trait evolution by accounting for both trait mean and variance. Here, we present a model of phenotypic trait evolution using a hierarchical Bayesian approach tha
Data from: Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits
- 负责人：
- DOI：
- doi:10.5061/dryad.8311n
- 摘要：
- d by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency
Data from: State-space modelling of the flight behaviour of a soaring bird provides new insights to migratory strategies
- 负责人：
- Pirotta, Enrico
- 关键词：
- 3D states GPS-GSM telemetry hidden state model Markov chain Monte Carlo movement ecology raptor subsidised flight
- DOI：
- doi:10.5061/dryad.44v9r82
- 摘要：
- energy. Increasing sophistication of tracking technologies paired with novel analytical approaches allows the characterisation of movement dynamics eve
Data from: Cladogenetic and anagenetic models of chromosome number evolution: a Bayesian model averaging approach
- 负责人：
- DOI：
- doi:10.5061/dryad.46m4b
- 摘要：
- of ancestral chromosome numbers over molecular phylogenies and generated new interest in studying the role of chromosome changes in evolution. Howeve
Data from: Postcopulatory sexual selection influences baculum evolution in primates and carnivores
- 负责人：
- DOI：
- doi:10.5061/dryad.412gv
- 摘要：
- s so far been elusive. Here, we use Markov chain Monte Carlo methods implemented in a Bayesian phylogenetic framework to reconstruct baculum evolution ac
Data from: Bayesian methods for estimating GEBVs of threshold traits
- 负责人：
- DOI：
- doi:10.5061/dryad.pp551
- 摘要：
- e correspondingly termed BayesTA, BayesTB and BayesTC?. Computing procedures of the three BayesT methods using Markov Chain Monte Carlo (MCMC) algorithm were derived
Data from: Bayes factors unmask highly variable information content, bias, and extreme influence in phylogenomic analyses
- 负责人：
- DOI：
- doi:10.5061/dryad.8gm85
- 摘要：
- as Markov chain Monte Carlo estimates of posterior probabilities). Bayes factors reveal important, previously hidden, differences across six “phylogenomic” data sets collecte
Data from: Bayesian hierarchical models for spatially misaligned data in R
- 负责人：
- 关键词：
- DOI：
- doi:10.5061/dryad.3g9s2
- 摘要：
- r and predictive inference within the proposed framework is illustrated using a synthetic and forest inventory data set. The proposed Markov chain Monte carlo
Data from: Marginal likelihood estimate comparisons to obtain optimal species delimitations in Silene sect. Cryptoneurae (Caryophyllaceae)
- 负责人：
- DOI：
- doi:10.5061/dryad.nj984
- 摘要：
- implemented in BEAST. To select among alternative species classification models a posterior simulation-based analog of the AIC through Markov chain Monte Carlo
Data from: Dispersal largely explains the Gondwanan distribution of the ancient tropical clusioid plant clade
- 负责人：
- DOI：
- doi:10.5061/dryad.q4h2r
- 摘要：
- and divergence times of the clusioid clade using a Bayesian Markov chain Monte Carlo approach. Ancestral Area Reconstructions (AARs) were then conducte
