pomp (version 0.39-3)

pmcmc-methods: Methods of the "pmcmc" class

Description

Methods of the "pmcmc" class.

Usage

## S3 method for class 'pmcmc':
logLik(object, \dots)
## S3 method for class 'pmcmc':
conv.rec(object, pars, \dots)
## S3 method for class 'pmcmc':
filter.mean(object, pars, \dots)
## S3 method for class 'pmcmc':
plot(x, y = NULL, \dots)
## S3 method for class 'pmcmc':
dprior(object, params, log = FALSE, \dots)
compare.pmcmc(z)

Arguments

object, x

The pmcmc object.

pars

Names of parameters.

y

Ignored.

z

A pmcmc object or list of pmcmc objects.

params

Named vector of parameters.

log

if TRUE, log probabilities are returned.

...

Further arguments (either ignored or passed to underlying functions).

References

C. Andrieu, A. Doucet and R. Holenstein, Particle Markov chain Monte Carlo methods, J. Roy. Stat. Soc B, to appear, 2010.

C. Andrieu and G.O. Roberts, The pseudo-marginal approach for efficient computation, Ann Stat 37:697-725, 2009.

See Also

pmcmc, pomp, pomp-class, pfilter