Gilmour9p

<p>Ilustrative data published in the original article (House prices)
Data with the practical meaning
Gilmour9p was taken from the original study (see Table1).</p>

data

Several methods may be found for selecting a subset of regressors from a set of k candidate variables in multiple linear regression.
One possibility is to evaluate all possible regression models and comparing them using Mallows's Cp statistic (Cp) according to Gilmour original study.
Full model is calculated, all possible combinations of regressors are generated, adjusted Cp for each submodel are computed, and the submodel with the minimum adjusted value Cp (ModelMin) is calculated.
To identify the final model, the package applies a sequence of hypothesis tests on submodels nested within ModelMin, following the approach outlined in Gilmour's original paper.
For more details see the help of the function final_model() and the original study (1996) <doi:10.2307/2348411>.

Josef Dolejs

gilmour

The Interpretation of Adjusted Cp Statistic

Gilmour9p function

<p>An object of class <code>data.frame</code> with 24 rows and 10 columns.</p>

Format

Author

Ilustrative data published in the original article (House prices)
Data with the practical meaning
Gilmour9p was taken from the original study (see Table1). — Gilmour9p

Ilustrative data published in the original article (House prices)
Data with the practical meaning
Gilmour9p was taken from the original study (see Table1).

Gilmour9p: Ilustrative data published in the original article (House prices) Data with the practical meaning Gilmour9p was taken from the original study (see Table1).

Description

Usage

Arguments

Format

Author

References