mclust (version 2.1-14)

clPairs: Pairwise Scatter Plots showing Classification

Description

Creates a scatter plot for each pair of variables in given data. Observations in different classes are represented by different symbols.

Usage

clPairs(data, classification, symbols, labels=dimnames(data)[[2]], 
        CEX=1, col, ...)

Arguments

data

A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables.

classification

A numeric or character vector representing a classification of observations (rows) of data.

symbols

Either an integer or character vector assigning a plotting symbol to each unique class classification. Elements in symbols correspond to classes in order of appearance in the sequence of observations (the order used b

labels

A vector of character strings for labeling the variables. The default is to use the column dimension names of data.

CEX

An argument specifying the size of the plotting symbols. The default value is 1.

col

Color vector to use. Default is one color per class. Splus default: all black.

...

Additional arguments to be passed to the graphics device.

Side Effects

Scatter plots for each combination of variables in data are created on the current graphics device. Observations of different classifications are labeled with different symbols.

References

C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington. See http://www.stat.washington.edu/mclust.

See Also

pairs, coordProj, mclustOptions

Examples

data(iris)
irisMatrix <- as.matrix(iris[,1:4])
irisClass <- iris[,5]

clPairs(irisMatrix, cl=irisClass, symbols=as.character(1:3))