ad.propSd: Adaptation For The Proposal Variance

In charlottedion/mixedsde: Estimation Methods for Stochastic Differential Mixed Effects Models

Description

Calculation of new proposal standard deviation

Usage

ad.propSd(chain, propSd, iteration, lower = 0.3, upper = 0.6,
  delta.n = function(n) min(0.1, 1/sqrt(n)))

Arguments

chain	vector of Markov chain samples
propSd	old proposal standard deviation
iteration	number of current iteration
lower	lower bound
upper	upper bound
delta.n	function for adding/subtracting from the log propSd

References

Rosenthal, J. S. (2011). Optimal proposal distributions and adaptive MCMC. Handbook of Markov Chain Monte Carlo, 93-112.

charlottedion/mixedsde documentation built on May 13, 2019, 3:35 p.m.