a0_gibbs_rate

BB_Likelihood_counts

BB_Prior_prob_phi

BB_Update_mu

BB_Update_phi

BB_Update_thetas

identify_invariant_loci

Initialize.params

Likelihood_counts

Likelihood_thetas

load_MCMC_output

load_posterior_predictive_samples

Prior_prob_alpha0

Prior_prob_alpha2

Prior_prob_alphaD

Prior_prob_alphaE

Prior_prob_beta

Prior_prob_mu

Shift

simulate_allele_count_data

transform_frequencies

Update_a0

Update_a2

Update_aD

Update_aE

Update_beta

Update_mu

Update_thetas

BEDASSLE-internal

Provides functions that allow users to quantify the relative
contributions of geographic and ecological distances to empirical patterns of genetic
differentiation on a landscape.  Specifically, we use a custom Markov chain
Monte Carlo (MCMC) algorithm, which is used to estimate the parameters of the
inference model, as well as functions for performing MCMC diagnosis and assessing
model adequacy.

Gideon Bradburd

BEDASSLE

Quantifies Effects of Geo/Eco Distance on Genetic
Differentiation

BEDASSLE-internal function

Internal BEDASSLE Functions — BEDASSLE-internal

Internal BEDASSLE Functions

BEDASSLE-internal: Internal BEDASSLE Functions

Description

Arguments

Details