Judge1


This  is a simulated dataset  containing information on  agricultural  products from six regions graded by 3 experts.
This dataset (Judge1) contains 4 symbolic interval variables. 
In these data, the five successive pairs of columns represented the five symbolic interval variables .
Each pair consists of a min and a max.


This package implements an extension of principal component analysis (PCA) tailored to handle multiple data tables. It can handle Big Data in the sense that the variation in massive data can be described by intervals [a, b] and multiple tables.

Brahim Brahim

GPCSIV

GPCSIV, Generalized Principal Component of Symbolic Interval
variables

Judge1 function

A data frame with 6 observations on the following 8 variables.
  <dl>
    <dt><code>Banana.min</code></dt><dd>a numeric vector, minimum grade banana proposed by the expert 1</dd> <dt><code>Banana.max</code></dt><dd>a numeric vector, maximum grade banana proposed by the expert 1</dd> <dt><code>Coffee.min</code></dt><dd>a numeric vector, minimum grade coffee proposed by the expert 1</dd> <dt><code>Coffee.max</code></dt><dd>a numeric vector, maximum grade coffee proposed by the expert 1</dd> <dt><code>Thea.min</code></dt><dd>a numeric vector, minimum grade thea proposed by the expert 1</dd> <dt><code>Thea.max</code></dt><dd>a numeric vector, maximum grade thea proposed by the expert 1</dd> <dt><code>Cocoa.min</code></dt><dd>a numeric vector, minimum grade cocoa proposed by the expert 1</dd> <dt><code>Cocoa.max</code></dt><dd>a numeric vector, maximum grade banana proposed by the expert 1</dd> </dl> 

Judge1: GPCSIV, dataset Judge 1

Description

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Examples