make.refFn: Make a reference function in bayou

Description Usage Arguments Details Value

View source: R/bayou-steppingstone.R


This function generates a reference function from a mcmc chain for use in marginal likelihood estimation.


make.refFn(chain, prior, burnin = 0.3, plot = TRUE)



An mcmc chain produced by bayou.mcmc() and loaded with load.bayou()


The prior function used to generate the mcmc chain


The proportion of the mcmc chain to be discarded when generating the reference function


Logical indicating whether or not a plot should be created


Distributions are fit to each mcmc chain and the best-fitting distribution is chosen as the reference distribution for that parameter using the method of Fan et al. (2011). For positive continuous parameters alpha, sigma^2, halflife, Vy, w2, Ne, Log-normal, exponential, gamma and weibull distributions are fit. For continuous distributions theta, Normal, Cauchy and Logistic distributions are fit. For discrete distributions, k, negative binomial, poisson and geometric distributions are fit. Best-fitting distributions are determined by AIC.


Returns a reference function of class "refFn" that takes a parameter list and returns the log density given the reference distribution. If plot=TRUE, a plot is produced showing the density of variable parameters and the fitted distribution from the reference function (in red).

bayou documentation built on May 29, 2017, 3:32 p.m.

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