Kernels

Wheat kernel data set taken from the UCI Machine Learning Repository

datasets

Routines for the graphical representation of correlation matrices by means of correlograms, MDS maps and biplots obtained by PCA, PFA or WALS (weighted alternating least squares); See Graffelman & De Leeuw (2023) <doi: 10.1080/00031305.2023.2186952>.

Jan Graffelman

Correlplot

A Collection of Functions for Graphing Correlation Matrices

Jan De Leeuw

Kernels function

A data frame with 210 observations on the following 8 variables.<dl>
 <dt><code>area</code></dt>
<dd>Area of the kernel</dd> <dt><code>perimeter</code></dt>
<dd>Perimeter of the kernel</dd> <dt><code>compactness</code></dt>
<dd>Compactness (C = 4*pi*A/P^2)</dd> <dt><code>length</code></dt>
<dd>Length of the kernel</dd> <dt><code>width</code></dt>
<dd>Width of the kernel</dd> <dt><code>asymmetry</code></dt>
<dd>Asymmetry coefficient</dd> <dt><code>groove</code></dt>
<dd>Length of the groove of the kernel</dd> <dt><code>variety</code></dt>
<dd>Variety (1=Kama, 2=Rosa, 3=Canadian)</dd> 
</dl>

Format

Wheat kernel data — Kernels

A data frame with 210 observations on the following 8 variables.<dl>
 <dt><code>area</code></dt>
<dd>Area of the kernel</dd>

 <dt><code>perimeter</code></dt>
<dd>Perimeter of the kernel</dd>

 <dt><code>compactness</code></dt>
<dd>Compactness (C = 4*pi*A/P^2)</dd>

 <dt><code>length</code></dt>
<dd>Length of the kernel</dd>

 <dt><code>width</code></dt>
<dd>Width of the kernel</dd>

 <dt><code>asymmetry</code></dt>
<dd>Asymmetry coefficient</dd>

 <dt><code>groove</code></dt>
<dd>Length of the groove of the kernel</dd>

 <dt><code>variety</code></dt>
<dd>Variety (1=Kama, 2=Rosa, 3=Canadian)</dd>

 
</dl>

Kernels: Wheat kernel data

Description

Usage

Arguments

Format

References

Examples