boa.randl {boa} | R Documentation |
Raftery and Lewis Convergence Diagnostics
Description
Computes the Raftery and Lewis convergence diagnostics for the parameters in an MCMC sequence.
Usage
boa.randl(link, q, error, prob, delta)
Arguments
link |
Matrix whose columns and rows contain the monitored parameters
and the MCMC iterations, respectively. The iteration numbers and parameter
names must be assigned to |
q |
Quantile to be estimated. |
error |
Desired amount of error in estimating the specified quantile 'q'. |
prob |
Probability of attaining the desired degree of error - 'error'. |
delta |
Delta value used in computing the convergence diagnostics. |
Value
A matrix whose columns and rows are the Raftery and Lewis convergence diagnostics (i.e. thin, burn-in, total, lower bound, and dependence factor) and the monitored parameters, respectively.
Author(s)
Brian J. Smith, Nicky Best, Kate Cowles
References
Raftery, A. L. and Lewis, S. (1992a). Comment: One long run with diagnostics: Implementation strategies for Markov chain Monte Carlo. Statistical Science, 7, 493-7.
Raftery, A. L. and Lewis, S. (1992b). How many iterations in the Gibbs sampler? In Bayesian Statistics 4, (ed. J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith), pp. 763-74. Oxford University Press.