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.

Tools for Building OLS Regression Models

package-ubuntu-20.04-r-4.0.5#cran#olsrr-0.5.3

<p>Identify outliers in cook's d plot.
</p>

<table summary="R argblock"><tr valign="top">
<td><code>k</code></td>
<td>
<p>Cooks' d bar plot data.</p>
</td>
</tr></table>

model <- lm(mpg ~ disp + hp + wt, data = mtcars)
k <- ols_prep_cdplot_data(model)
ols_prep_outlier_obs(k)

package-ubuntu-20.04-r-4.0.5#cran#olsrr-0.5.3#docs#ols_prep_outlier_obs

ols_prep_outlier_obs

Description

Usage

Arguments

Examples

olsrr

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