bootstrap_gmmsslm {gmmsslm}

Bootstrap Analysis for gmmsslm

Description

This file provides functions to perform bootstrap analysis on the results of the gmmsslm function.

This function performs non-parametric bootstrap to assess the variability of the gmmsslm function outputs.

Usage

bootstrap_gmmsslm(
  dat,
  zm,
  pi,
  mu,
  sigma,
  paralist,
  xi,
  type,
  iter.max = 500,
  eval.max = 500,
  rel.tol = 1e-15,
  sing.tol = 1e-15,
  B = 2000
)

Arguments

dat

A matrix where each row represents an individual observation.

zm

A matrix or data frame of labels corresponding to dat.

pi

A numeric vector representing the mixing proportions.

mu

A matrix representing the location parameters.

sigma

An array representing the covariance matrix or list of covariance matrices.

paralist

A list of parameters.

xi

A numeric value representing the coefficient for a logistic function of the Shannon entropy.

type

A character value indicating the type of Gaussian mixture model.

iter.max

An integer indicating the maximum number of iterations.

eval.max

An integer indicating the maximum number of evaluations.

rel.tol

A numeric value indicating the relative tolerance.

sing.tol

A numeric value indicating the singularity tolerance.

B

An integer indicating the number of bootstrap samples.

Value

A list containing mean and sd of bootstrap samples for pi, mu, sigma, and xi.