rubber

The data come from an experiment to investigate how the resistance of rubber 
to abrasion is affected by the hardness of the rubber and its tensile strength.

datasets

Best subset glm using information criteria or cross-validation,
carried by using 'leaps' algorithm (Furnival and Wilson, 1974) <doi:10.2307/1267601>
or complete enumeration (Morgan and Tatar, 1972) <doi:10.1080/00401706.1972.10488918>.
Implements PCR and PLS using AIC/BIC.
Implements one-standard deviation rule for use with the 'caret' package.

Yuanhao Lai

bestglm

Best Subset GLM and Regression Utilities

rubber function

A data frame with 30 observations on the following 3 variables.<dl class="dl-horizontal">
 <dt><code>hardness</code></dt><dd>hardness in degree Shore</dd>
 <dt><code>tensile.strength</code></dt><dd>tensile strength in kg per square meter</dd>
 <dt><code>abrasion.loss</code></dt><dd>abrasion loss in gram per hour</dd>
 <dt><code>ts.low</code></dt><dd>tensile strength minus the breakpoint 180 km/m^2</dd>
 <dt><code>ts.high</code></dt><dd>tensile strength minus the breakpoint 180 km/m^2</dd>
 </dl>

Format

Abrasion loss for various hardness and tensile strength — rubber

A data frame with 30 observations on the following 3 variables.<dl class='dl-horizontal'>
 <dt><code>hardness</code></dt><dd>hardness in degree Shore</dd>
 <dt><code>tensile.strength</code></dt><dd>tensile strength in kg per square meter</dd>
 <dt><code>abrasion.loss</code></dt><dd>abrasion loss in gram per hour</dd>
 <dt><code>ts.low</code></dt><dd>tensile strength minus the breakpoint 180 km/m^2</dd>
 <dt><code>ts.high</code></dt><dd>tensile strength minus the breakpoint 180 km/m^2</dd>
 </dl>

rubber: Abrasion loss for various hardness and tensile strength

Description

Usage

Arguments

Format

References

Examples