cooks_test

<code>cooks_test</code> returns the observations identified
as influential based on the cooks statistics being
larger than a threshold. The threshold for this
test is the <code>0.5</code>
quantile of a \(F_{p, n-p}\) distribution
where \(p = \)<code>length(stats::coef(model))</code> and
\(n - p = \)<code>stats::df.residual(model)</code>.

Simplifies aspects of linear regression analysis, particularly simultaneous inference. Additionally, supports "A Progressive Introduction to Linear Models" by Joshua French (<https://jfrench.github.io/LinearRegression/>).

Joshua French

api2lm

Functions and Data Sets for the Book "A Progressive Introduction
to Linear Models"

cooks_test function

<dl><dt>model</dt>
<dd>A fitted model object from the
<code><a href="/link/lm?package=api2lm&version=0.2" data-mini-rdoc="api2lm::lm">lm</a></code> function.</dd>
<dt>n</dt>
<dd>The number of outliers to return. The default is
all influential observations.</dd></dl>

Arguments

<code>cooks_test</code> returns the observations identified
as influential based on the cooks statistics being
larger than a threshold. The threshold for this
test is the <code>0.5</code>
quantile of a \(F_{p, n-p}\) distribution
where \(p = \)<code>length(stats::coef(model))</code> and
\(n - p = \)<code>stats::df.residual(model)</code>.

Identify influential observations — cooks_test

<dl>

<dt>model</dt>
<dd>A fitted model object from the
<code><a href='https://rdrr.io/r/stats/lm.html'>lm</a></code> function.</dd>


<dt>n</dt>
<dd>The number of outliers to return. The default is
all influential observations.</dd>

</dl>

cooks_test: Identify influential observations

Description

Usage

Value

Arguments

See Also

Examples