psp_control {psp} | R Documentation |
psp_control
allows users to define characteristics of the
parameter space partitioning MCMC algorithm as implemented in
psp_global
.
psp_control(radius = 0.1, init = NULL, lower, upper,
pop = 400, cl = NULL,
param_names = NULL,
parallel = TRUE,
cluster_names = NULL,
iterations = 1000)
radius |
The radius of the hypershere with n-dimensions to sample from. Must be a double. Default is 0.1. |
init |
A vector of parameters to use as the first jumping distribution.
If |
lower , upper |
Vectors specifiying the lower and upper boundaries of the parameter space for each parameter. The i-th element of lower and upper bounds applies to the i-th parameter. |
pop |
The minimum population psp_global aims to find for each ordinal
pattern discovered. This can stop the parameter search early in case
the population of all ordinal pattern are equal to or larger than |
parallel |
If TRUE (default), uses the parallel package to run evaluations of jumping distributions for each chain parallel. |
cl |
If parallel is TRUE, the number of cores to use for
|
param_names |
A character vector that includes the names of each
parameter. If |
cluster_names |
A character vector that includes the list of functions
to be loaded into each cluster. Default is |
.
iterations |
The number of global iterations for psp_global. Default is 1000. |
Returns a control list suitable for psp_global
with the above
elements.
# two parameter model
psp_control(lower = rep(0, 2), upper = rep(1, 2), init = rep(0.5, 2),
radius = rep(0.25, 2), cluster_names = NULL,
parallel = FALSE, iterations = 500)