replicate_under_ci: Bootstrap replication under the null hypothesis

In lg: Locally Gaussian Distributions: Estimation and Methods

Description

Generate bootstrap replicates under the null hypothesis that the first two variables are conditionally independent given the rest of the variables.

Usage

replicate_under_ci(lg_object, n_rep, nodes, M = NULL, M_sim = 1500,
  M_corr = 1.5, n_corr = 1.2, extend = 0.3)

Arguments

lg_object	An object of type lg, as produced by the lg_main-function
n_rep	The number of replicated bootstrap samples
nodes	Either the number of equidistant nodes to generate, or a vector of nodes supplied by the user
M	The value for M in the accept-reject algorithm if already known
M_sim	The number of replicates to simulate in order to find a value for M
M_corr	Correction factor for M, to be on the safe side
n_corr	Correction factor for n_new, so that we mostly will generate enough observations in the first go
extend	How far to extend the grid beyond the extreme data points when interpolating, in share of the range

lg documentation built on Dec. 5, 2019, 5:13 p.m.