ols_test_outlier

Detect outliers using Bonferroni p values.

Tools designed to make it easier for users, particularly beginner/intermediate R users
to build ordinary least squares regression models. Includes comprehensive regression output,
heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence,
model fit assessment and variable selection procedures.

Aravind Hebbali

olsrr

Tools for Building OLS Regression Models

ols_test_outlier function

<dl><dt>model</dt>
<dd>An object of class <code>lm</code>.</dd>
<dt>cut_off</dt>
<dd>Bonferroni p-values cut off for reporting observations.</dd>
<dt>n_max</dt>
<dd>Maximum number of observations to report, default is 10.</dd>
<dt>...</dt>
<dd>Other arguments.</dd></dl>

Arguments

Bonferroni Outlier Test — ols_test_outlier

<dl>

<dt>model</dt>
<dd>An object of class <code>lm</code>.</dd>


<dt>cut_off</dt>
<dd>Bonferroni p-values cut off for reporting observations.</dd>


<dt>n_max</dt>
<dd>Maximum number of observations to report, default is 10.</dd>


<dt>...</dt>
<dd>Other arguments.</dd>

</dl>

ols_test_outlier: Bonferroni Outlier Test

Description

Usage

Arguments

Examples