rcrmtvnorm

Draws from a multivariate normal distribution, rejecting any samples
outside the confidence region defined by alpha.

internal

Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <doi:10.48550/arXiv.1412.5000>,
and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <doi:10.48550/arXiv.1605.06566>
for testing whether there is unexplained variation in treatment effects across observations, and for characterizing
the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions
implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test.

Ben Fifield

hettx

Fisherian and Neymanian Methods for Detecting and Measuring
Treatment Effect Variation

Peng Ding

Avi Feller

Luke Miratrix

rcrmtvnorm function

<dl><dt>n</dt>
<dd>Number of draws to generate.</dd>
<dt>mu</dt>
<dd>Mean vector.</dd>
<dt>sigma</dt>
<dd>Covariance matrix.</dd>
<dt>alpha</dt>
<dd>Tail probability to exclude (defines the chi-squared confidence region).</dd></dl>

Arguments

Generate truncated multivariate normal draws — rcrmtvnorm

<dl>

<dt>n</dt>
<dd>Number of draws to generate.</dd>


<dt>mu</dt>
<dd>Mean vector.</dd>


<dt>sigma</dt>
<dd>Covariance matrix.</dd>


<dt>alpha</dt>
<dd>Tail probability to exclude (defines the chi-squared confidence region).</dd>

</dl>

rcrmtvnorm: Generate truncated multivariate normal draws

Description

Usage

Value

Arguments