ols_plot_resid_regressor

Graph to determine whether we should add a new predictor to the model already
containing other predictors. The residuals from the model is regressed on the
new predictor and if the plot shows non random pattern, you should consider
adding the new predictor to the model.

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_plot_resid_regressor function

<dl><dt>model</dt>
<dd>An object of class <code>lm</code>.</dd>
<dt>variable</dt>
<dd>New predictor to be added to the <code>model</code>.</dd>
<dt>print_plot</dt>
<dd>logical; if <code>TRUE</code>, prints the plot else returns a plot object.</dd></dl>

Arguments

Residual vs regressor plot — ols_plot_resid_regressor

<dl>

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


<dt>variable</dt>
<dd>New predictor to be added to the <code>model</code>.</dd>


<dt>print_plot</dt>
<dd>logical; if <code>TRUE</code>, prints the plot else returns a plot object.</dd>

</dl>

ols_plot_resid_regressor: Residual vs regressor plot

Description

Usage

Arguments

See Also

Examples