theil

Henri Theil's textile consumption data modified.

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

theil function

A data set with 17 observations in relation to the following five variables:<dl>
 <dt><code>obs</code></dt>
<dd>Year.</dd> <dt><code>consume</code></dt>
<dd>Volume of textile consumption per capita (base 1925=100).</dd> <dt><code>income</code></dt>
<dd>Real Income per capita (base 1925=100).</dd> <dt><code>relprice</code></dt>
<dd>Relative price of textiles (base 1925=100).</dd> <dt><code>twentys</code></dt>
<dd>Dummy variable that differentiates between the twenties and thirties.</dd> 
</dl>

Format

Henri Theil data — theil

A data set with 17 observations in relation to the following five variables:<dl>
 <dt><code>obs</code></dt>
<dd>Year.</dd>

 <dt><code>consume</code></dt>
<dd>Volume of textile consumption per capita (base 1925=100).</dd>

 <dt><code>income</code></dt>
<dd>Real Income per capita (base 1925=100).</dd>

 <dt><code>relprice</code></dt>
<dd>Relative price of textiles (base 1925=100).</dd>

 <dt><code>twentys</code></dt>
<dd>Dummy variable that differentiates between the twenties and thirties.</dd>

 
</dl>

theil: Henri Theil data

Description

Usage

Arguments

Format

Details

References

Examples