Klein and Goldberger data on consumption and wage income.

datasets

The detection of worrying approximate collinearity in a multiple linear regression model is a problem addressed in all existing statistical packages. However, we have detected deficits regarding to the incorrect treatment of qualitative independent variables and the role of the intercept of the model. The objective of this package is to correct these deficits. In this package will be available detection and treatment techniques traditionally used as the recently developed.

R. Salmeron

multiColl

Collinearity Detection in a Multiple Linear Regression Model

KG function

A data frame with 14 observations in relation to the following four variables:<dl>
 <dt><code>consumption</code></dt>
<dd>Domestic consumption.</dd> <dt><code>wage.income</code></dt>
<dd>Wage income.</dd> <dt><code>non.farm.income</code></dt>
<dd>Non-wage-non-farm income.</dd> <dt><code>farm.income</code></dt>
<dd>Farm income.</dd> 
</dl>

Format

Klein and Goldberger data — KG

A data frame with 14 observations in relation to the following four variables:<dl>
 <dt><code>consumption</code></dt>
<dd>Domestic consumption.</dd>

 <dt><code>wage.income</code></dt>
<dd>Wage income.</dd>

 <dt><code>non.farm.income</code></dt>
<dd>Non-wage-non-farm income.</dd>

 <dt><code>farm.income</code></dt>
<dd>Farm income.</dd>

 
</dl>

KG: Klein and Goldberger data

Description

Usage

Arguments

Format

Details

References

Examples