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This function initiates the Markov chain Monte Carlo (MCMC) for the beta-binomial BEDASSLE model. The beta-binomial model allows populations to diverge from the model's expectations based on their location and their neighbors.
● Data Source:
CranContrib
● Keywords:
● Alias: MCMC_BB
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This function initiates the Markov chain Monte Carlo (MCMC) for the binomial BEDASSLE model.
● Data Source:
CranContrib
● Keywords:
● Alias: MCMC
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This function calculates unbiased F_{ST} (based on Weir and Hill's θ, 2002), between a pair of populations/individuals. Loci for which either of the populations/individuals has missing data (i.e. - the sample size is zero) are excluded.
● Data Source:
CranContrib
● Keywords:
● Alias: calculate.pairwise.Fst
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Creates a series of plots showing the proportion of proposed moves to accepted moves over the duration of the MCMC analysis for each parameter updated via a random-walk sampler.
● Data Source:
CranContrib
● Keywords:
● Alias: plot_all_acceptance_rates
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This function simulates data using the inference model parameterized from the joint posterior of the MCMC and the observed independent variables (D_{ij} and E_{ij}). These posterior predictive samples can be compared to the observed data to see how well the model is able to describe the observed data.
● Data Source:
CranContrib
● Keywords:
● Alias: posterior.predictive.sample
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Creates a plot showing the proportion of proposed moves to accepted moves over the duration of the MCMC analysis.
● Data Source:
CranContrib
● Keywords:
● Alias: plot_acceptance_rate
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Plots the posterior marginal densities of all phi parameters. Users may specify whether they want a histogram, a density, or both. For convenience, the F_{k} statistic is presented in place of the phi parameter, as this is the statistic users care about. F_{k} is defined as frac{1}{1+phi_{k}}.
● Data Source:
CranContrib
● Keywords:
● Alias: plot_all_phi_marginals
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This function plots the parameter value estimated in each sampled generation of the MCMC against the index of that sampled generation for each parameter in the model.
● Data Source:
CranContrib
● Keywords:
● Alias: plot_all_trace
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This function plots the posterior predictive samples generated by posterior.predictive.sample around the observed data, so that users can evaluate how well the model is able to describe their data.
● Data Source:
CranContrib
● Keywords:
● Alias: plot_posterior_predictive_samples
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This method models the covariance in allele frequencies between populations on a landscape as a decreasing function of their pairwise geographic and ecological distance. Allele frequencies are modeled as a spatial Gaussian process with a parametric covariance function. The parameters of this covariance function, as well as the spatially smoothed allele frequencies, are estimated in a custom Markov chain Monte Carlo.
● Data Source:
CranContrib
● Keywords:
● Alias: BEDASSLE, BEDASSLE-package
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