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Data from: A hierarchical Bayesian approach for handling missing classification data
负责人:
关键词:
N-mixture model;elk;wildlife;Cervus elaphus nelsoni;Hierarchical Bayesian Statistics;abundance;Multi-State Mark-Recapture;population size
DOI:
doi:10.5061/dryad.8h36t01
摘要:
. We developed two hierarchical Bayesian models to overcome the assumption of perfect assignment to mutually exclusive categories in the multinomia
Data from: The consequences of not accounting for background selection in demographic inference
负责人:
关键词:
Natural Selection and Contemporary Evolution;Evolutionary Theory;Population Genetics - Theoretical;population dynamics
DOI:
doi:10.5061/dryad.37hc1
摘要:
Recently, there has been increased awareness of the role of background selection (BGS) in both data analysis and modelling advances. However, BGS
Data from: Identifying drivers of spatial variation in occupancy with limited replication camera trap data
负责人:
关键词:
occupancy model;Bayesian modeling;Serengeti;camera trap
DOI:
doi:10.5061/dryad.34kb373
摘要:
nt ecological quantities. These models account for imperfect detection using a latent variable to distinguish between true presence/absence and observed
Data from: Causal reasoning in rats' behaviour systems
负责人:
关键词:
Bayesian networks;Rattus norvegicus;cognitive modelling;causal reasoning;behaviour systems;Causal Model Theory
DOI:
doi:10.5061/dryad.20h4r
摘要:
e assumptions, with formal help from Bayesian Networks, self-production of the Tone should reduce expectation of alternative causes, including Light, and thei
Data from: Total-evidence dating under the fossilized birth-death process
负责人:
关键词:
Bayesian phylogenetic inference;relaxed clock;MCMC;birth-death process;total-evidence dating;tree prior
DOI:
doi:10.5061/dryad.26820
摘要:
s been used to model speciation, extinction and fossilization rates that can vary over time in a piecewise manner. So far, sampling of extant and fossil taxa
Data from: Penalized likelihood methods improve parameter estimates in occupancy models
负责人:
关键词:
penalized likelihood;boundary estimates;maximum likelihood;summer 2011;occupancy modeling;detection probability;parameter estimation
DOI:
doi:10.5061/dryad.t40f2
摘要:
in ridge regression and Bayesian approaches, and we compare them to a penalty developed for occupancy models in prior work. 3. We examine the bias, varia
Data from: Assessing parameter identifiability in phylogenetic models using Data Cloning
负责人:
关键词:
Data Cloning;Bayesian estimation in Phylogenetics;Parameter Identifiability;maximum likelihood
DOI:
doi:10.5061/dryad.rr6400b4
摘要:
ty while investigating complex modeling scenarios, where getting closed-form expressions in a probabilistic study is complicated. Furthermore, here we also show how DC
Data from: Using camera trapping and hierarchical occupancy modelling to evaluate the spatial ecology of an African mammal community
负责人:
关键词:
multi-species modelling;multi-species modeling;species richness;biodiversity;Grasslands;hierarchical Bayesian models;protected areas;Body Size;human disturbance;diet;camera trap
DOI:
doi:10.5061/dryad.q54rp
摘要:
. We demonstrate the utility of hierarchical Bayesian models for assessing community, group and individual species’ responses to anthropogenic
Fully Bayesian Analysis of RNA-seq Counts for the Detection of Gene Expression Heterosis
负责人:
关键词:
Genetics Molecular Biology Biotechnology 69999 Biological Sciences not elsewhere classified 19999 Mathematical Sciences not elsewhere classified 110309 Infectious Diseases Plant Biology
DOI:
doi:10.6084/m9.figshare.6949499
摘要:
distributions for p-values under these null hypotheses. Thus, we develop a general hierarchical model for count data and a fully Bayesian analysis in which an efficient
Data from: ABC inference of multi-population divergence with admixture from unphased population genomic data
负责人:
关键词:
gene flow;phylogeography;approximate Bayesian computation (ABC);Biorhiza pallida;Next Generation Sequencing;speciation
DOI:
doi:10.5061/dryad.80m5b
摘要:
in non-model systems. Inferential tools for historical demography given these datasets are, at present, underdeveloped. In particular, approximate Bayesian

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