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 \(\frac{1}{1+phi_{k}}\).
plot_all_phi_marginals(phi_mat, percent.burnin = 0, thinning = 1,
population.names = NULL, pop.index= NULL, histogram = TRUE, density = TRUE)
The k by ngen matrix of phi values estimated for all k
populations/individuals included in the analysis in each of ngen MCMC
generations.
The percent of the sampled MCMC generations to be discarded as "burn-in." If the
MCMC is run for 1,000,000 generations, and sampled every 1,000 generations, there
will be 1,000 sampled generations. A percent.burnin of 20 will discard
the first 200 sampled parameter values from that sample.
The multiple by which the sampled MCMC generations are thinned. A thinning of
5 will sample every 5th MCMC generation.
A vector of length k, where k is the number of populations/individuals
(i.e. k = nrow(counts)), giving the name or identifier of each
population/individual included in the analysis. These will be used to title the
k
trace plots of the phi parameters estimated for each population/individual in the
beta-
binomial model. If population.names is not provided (i.e.
population.names =
NULL),
a population index number will be used to title the plot.
A population index number generated to title a marginal plot if no
population.names
is specified.
A switch that controls whether or not the plot contains a histogram of the values
estimated for the parameter over the course of the MCMC. Default is TRUE.
A switch that controls whether or not the plot shows the density of the values
estimated for the parameter over the course of the MCMC. Default is TRUE.
Gideon Bradburd
The marginal plot is another basic visual tool for MCMC diagnosis. Users should look for marginal plots that are "smooth as eggs" (indicating that the chain has been run long enough) and unimodal (indicating a single peak in the likelihood surface).