plot_acceptance_rate: Plots the acceptance rate of a parameter across MCMC...
In BEDASSLE: Quantifies Effects of Geo/Eco Distance on Genetic Differentiation

plot_acceptance_rate

R Documentation

Plots the acceptance rate of a parameter across MCMC generations

Description

Creates a plot showing the proportion of proposed moves to accepted moves over the duration of the MCMC analysis.

Usage

plot_acceptance_rate(accepted.moves, proposed.moves, param.name =
deparse(substitute(accepted.moves)))

Arguments

`accepted.moves`	A vector giving the number of accepted random-walk moves at each sampled MCMC generation.
`proposed.moves`	A vector giving the number of proposed random-walk moves at each sampled MCMC generation.
`param.name`	The name of the parameter for which the trace plot is being displayed.

Details

For optimal mixing, between ~20 samplers should be accepted. If the acceptance rates fall outside that range, this function will automatically highlight that parameter as a potential instance of poor mixing. If the acceptance rates are too low, then for subsequent analyses the user should decrease the scale of the tuning parameter (or "std," as in, e.g., "aD_std"), and if acceptance rates are too high, the user should increase the scale of the tuning parameter. The scale of the tuning parameter is the standard deviation of the normal distribution from which the small random variable is drawn and added to the current parameter value to propose a move. If the acceptance rate has not plateaued by the end of an analysis, it is an indication that the chain may still be "going somewhere" in parameter space, and subsequent analyses should be performed.