Description Objects from the Class Slots Methods Author(s) See Also Examples
This class holds parameters for the Sequential Monte Carlo sampler.
Objects can be created by calls of the function "smcparameters"
.
nparticles
:Object of class "numeric"
: an integer
representing the desired number of particles.
temperatures
:Object of class "numeric"
: a vector of temperatures, default being
"seq(from = 0.01, to = 1, length.out = 100)"
.
nmoves
:Object of class "numeric"
: number of move steps to be performed after each
resampling step, default being 1.
ESSthreshold
:Object of class "numeric"
: resampling occurs when the Effective Sample Size
goes below "ESSthreshold"
multiplied by the number of particles "nparticles"
.
movetype
:Object of class "character"
: type of Metropolis-Hastings move step to be performed;
can be either set to "independent"
or "randomwalk"
, default being "independent"
.
movescale
:Object of class "numeric"
: if movetype
is set to "randomwalk"
, this parameter
specifies the amount by which the estimate of the standard deviation of the target distribution is multiplied; the product
being used to propose new points in the random-walk MH step. Default is 10%, ie a new point is proposed from a Normal
distribution, centered on the latest point, with standard deviation equal to 10% of the standard deviation of the already-generated
chain.
resamplingscheme
:Object of class "character"
: type of resampling to be used; either "multinomial", "residual"
or "systematic", the default being "systematic".
signature(object = "smcparameters")
: provides a little summary of a binning object when called (or when print
is called).
Luke Bornn <bornn@stat.harvard.edu>, Pierre E. Jacob <pierre.jacob.work@gmail.com>
1 2 3 4 5 | showClass("smcparameters")
smcparam<- smcparameters(nparticles=5000,
temperatures = seq(from = 0.0001, to = 1, length.out= 100),
nmoves = 5, ESSthreshold = 0.5, movetype = "randomwalk",
movescale = 0.1)
|
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