ad.propSd_random {mixedsde}

Adaptation For The Proposal Variance

Description

Calculation of new proposal standard deviation for the random effects

Usage

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

Arguments

chain

matrix 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.