smc: Sequential Monte Carlo

In PAWL: Implementation of the PAWL algorithm

Description

Sequential Monte Carlo samplers, using a sequence of tempered distributions.

Usage

smc(target, AP, verbose)

Arguments

target	Object of class target: specifies the target distribution. See the help of target. The target must be defined on a continuous state space.
AP	Object of class "smcparameters": specifies the number of particles, the ESS threshold, the sequence of distributions, etc. See the help of smcparameters.
verbose	Object of class "logical": if TRUE (default) then prints some indication of progress in the console.

Value

The function returns a list holding various information:

particles	a matrix with rows representing particles and columns components of each particle.
weights	a vector of weights associated to each particle. See also the convenience function normalizeweight.
ESSarray	a vector of the ESS computed at each iteration.
resamplingtimes	a vector indicating the iteration at which resampling was performed.

Author(s)

Luke Bornn <[e-mail]>, Pierre E. Jacob <[e-mail]>

See Also

smcparameters

PAWL documentation built on May 2, 2019, 5:58 a.m.