boot.mple: Bootstrap resampling for MPLE

In NScluster: Simulation and Estimation of the Neyman-Scott Type Spatial Cluster Models

Bootstrap resampling for MPLE

Description

Carry out bootstrap replicates of MPLE on simulated data.

Usage

boot.mple(mple.out, n = 100, conf.level = 0.95, se = TRUE, trace = FALSE)

## S3 method for class 'boot.mple'
summary(object, ...)

Arguments

mple.out	an object of class "mple", usually the result of a call to mple.cppm.
n	number of bootstrap replicates performed.
conf.level	the confidence level required.
se	logical. If TRUE standard errors are returned.
trace	logical: if TRUE, a progress bar is shown.
object	an object of class "boot.mple".
...	ignored.

Value

boot.mple returns an object of class "boot.mple" containing the following components:

boot.mples	a matrix of n rows each of which is a bootstrap replicate of the result of calling mple.cppm.
confint	confidence intervals for MPLEs.
mple	MPLE of mple.out passed as 'pars' argument to sim.cppm.

Examples

### Thomas Model
# simulation
pars <- c(mu = 50.0, nu = 30.0, sigma = 0.03)
t.sim <- sim.cppm("Thomas", pars, seed = 117)

## Not run:  # estimation (need long CPU time)
init.pars <- c(mu = 40.0, nu = 40.0, sigma = 0.05)
t.mple <- mple.cppm("Thomas", t.sim$offspring$xy, init.pars)
t.boot <- boot.mple(t.mple)
summary(t.boot)

## End(Not run)

NScluster documentation built on March 31, 2023, 5:14 p.m.