gen_boot_sample

The matrix of Normal observations with independent
observations from a normal with an identity Covariance matrix.

epsilon_mat

The empirical estimate of the influence curve to be
used in the multiplier bootstrap.

obs_ic

Boolean. If true, the bootstrapped data will be centered at
zero. Otherwise, it will be centered at param_est.

center

The estimated parameters which will be the mean of the
multiplier bootstrap sample.

param_est

Normalizing constant. Should either be <code>"n"</code> or
<code>"rootn"</code>.

rate

Number of desired observations from your bootstrapped sample.

A helper function to generate a multiplier bootstrap sample

A testing framework for testing the multivariate point null hypothesis.
A testing framework described in Elder et al. (2022) <arXiv:2203.01897> to test the multivariate point null hypothesis. After the user selects a parameter of interest and defines the assumed data generating mechanism, this information should be encoded in functions for the parameter estimator and its corresponding influence curve. Some parameter and data generating mechanism combinations have codings in this package, and are explained in detail in the article.

gen_boot_sample: A helper function to generate a multiplier bootstrap sample

Description

Usage

Arguments

Value