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.
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
)A list containing mean and sd of bootstrap samples for pi, mu, sigma, and xi.
A matrix where each row represents an individual observation.
A matrix or data frame of labels corresponding to dat.
A numeric vector representing the mixing proportions.
A matrix representing the location parameters.
An array representing the covariance matrix or list of covariance matrices.
A list of parameters.
A numeric value representing the coefficient for a logistic function of the Shannon entropy.
A character value indicating the type of Gaussian mixture model.
An integer indicating the maximum number of iterations.
An integer indicating the maximum number of evaluations.
A numeric value indicating the relative tolerance.
A numeric value indicating the singularity tolerance.
An integer indicating the number of bootstrap samples.