psp_control: Control the behaviour of the psp_global implementation

Description Usage Arguments Value See Also Examples

View source: R/psp_global.R

Description

psp_control allows user to define characteristics of the parameter space partitioning MCMC algorithm as implemented in psp_global.

Usage

1
2
3
4
5
psp_control(radius = 0.1, init = NULL, lower, upper,
           pop = 400, cl = NULL,
           param_names = NULL,
           cluster_names = NULL,
           iterations = 1000)

Arguments

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 NULL (default), parameter search starts from the center of the parameter space.

lower, upper

Vectors spercifiying the lower and upper boundaries of the parameter space for each parameter. The i-th element of lower and upper 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 each ordinal pattern are equal to or larger than pop. If you do not want to use this option, set it to NULL or Inf. Default is 400.

cl

The number of cores to use for makeCluster from the parallel pacakge.

param_names

A character vector that includes the names of each parameter. If NULL (default), a character vector is generated with parameter_1, parameter_2, parameter_3", ...

cluster_names

A character vector that includes the list of functions to be loaded into each parallel cluster. Default is NULL

.

iterations

The number of global iterations for psp_global. Default is 1000.

Value

Returns a control list suitable for psp_global with the above elements.

See Also

psp_global.

Examples

1
2
3
# 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, iterations = 500)

lenarddome/psp documentation built on May 1, 2021, 7:09 p.m.