MLPB3: Multivariate Linear Bootstrapping - core function

In dfConn: Dynamic Functional Connectivity Analysis

Description

Multivariate Linear Bootstrapping - core function

Usage

MLPB3(X, Boot, l = 1, eps = 1, beta = 1, l_automatic = 0,
  l_automatic_local = 0)

Arguments

X	data matrix
Boot	integer, number of bootstrap samples to be generated
l	numeric, the banding parameter, default is 1
eps	numeric the parameters for making Gamma_kappa_matrix positive definite if necessary, default is 1;
beta	numeric the parameters for making Gamma_kappa_matrix positive definite if necessary, default is 1;
l_automatic	numeric the banding parameter, default is 1, data-adaptively;
l_automatic_local	numeric, the banding parameter default is 0

Value

a numeric matrix with n*boot rows and m columns, where n, m refer to the number of rows and number of columns in input data matrix, and boot refer to number of bootstrap samples to be generated.

Examples

# Multivariate linear bootstrapping on a random matrix with 2 rows and 4 columns
MLPB3(matrix(rnorm(16),2,4), 3)

dfConn documentation built on June 14, 2019, 1:02 a.m.