proposals {pomp} | R Documentation |
Functions to construct proposal distributions for use with MCMC methods.
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
)
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 |
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.
Aaron A. King, Sebastian Funk
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.
More on Markov chain Monte Carlo methods:
abc()
,
pmcmc()