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>Data for generating residual fit spread plot.
</p>

ols_prep_rfsplot_fmdata(model)

ols_prep_rfsplot_rsdata(model)

<table summary="R argblock"><tr valign="top">
<td><code>model</code></td>
<td>
<p>An object of class <code>lm</code>.</p>
</td>
</tr></table>

model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_prep_rfsplot_fmdata(model)
ols_prep_rfsplot_rsdata(model)

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

ols_prep_rfsplot_fmdata

Description

Usage

Arguments

Examples

olsrr

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