ad.propSd: Adaptation For The Proposal Variance

Description Usage Arguments References

Description

Calculation of new proposal standard deviation

Usage

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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.