test_u_normal

Test a sample against the null hypothesis that it comes from a standard Normal distribution with the specified test.

Implements the Agnostic Fay-Herriot model, an extension of
the traditional small area model. In place of normal sampling errors, the
sampling error distribution is estimated with a Gaussian process to
accommodate a broader class of distributions. This flexibility is most
useful in the presence of bounded, multi-modal, or heavily skewed sampling
errors.

Marten Thompson

agfh

Agnostic Fay-Herriot Model for Small Area Statistics

Snigdhansu Chatterjee

test_u_normal function

<dl> <dt>samples</dt>
<dd>vector of values to be tested</dd> <dt>test</dt>
<dd>name of test, one of <code>'SW'</code>, <code>'KS'</code>, <code>'CM'</code>, <code>'AD'</code></dd></dl>

Arguments

Normality Test — test_u_normal

<dl>

 <dt>samples</dt>
<dd>vector of values to be tested</dd>

 <dt>test</dt>
<dd>name of test, one of <code>'SW'</code>, <code>'KS'</code>, <code>'CM'</code>, <code>'AD'</code></dd>

</dl>

test_u_normal: Normality Test

Description

Usage

Value

Arguments

Details

Examples