proposals {pomp} | R Documentation |
MCMC proposal distributions
Description
Functions to construct proposal distributions for use with MCMC methods.
Usage
mvn_diag_rw(rw.sd)
mvn_rw(rw.var)
mvn_rw_adaptive(
rw.sd,
rw.var,
scale.start = NA,
scale.cooling = 0.999,
shape.start = NA,
target = 0.234,
max.scaling = 50
)
Arguments
rw.sd |
named numeric vector; random-walk SDs for a multivariate normal random-walk proposal with diagonal variance-covariance matrix. |
rw.var |
square numeric matrix with row- and column-names. Specifies the variance-covariance matrix for a multivariate normal random-walk proposal distribution. |
scale.start , scale.cooling , shape.start , target , max.scaling |
parameters
to control the proposal adaptation algorithm. Beginning with MCMC
iteration |
Value
Each of these calls constructs a function suitable for use as the
proposal
argument of pmcmc
or abc
. Given a parameter
vector, each such function returns a single draw from the corresponding
proposal distribution.
Author(s)
Aaron A. King, Sebastian Funk
References
G.O. Roberts and J.S. Rosenthal. Examples of adaptive MCMC. Journal of Computational and Graphical Statistics 18, 349–367, 2009. doi:10.1198/jcgs.2009.06134.
See Also
More on Markov chain Monte Carlo methods:
abc()
,
pmcmc()