Creates a scatter plot for each pair of variables in given data. Observations in different classes are represented by different colors and symbols.
clPairs(data, classification, symbols, colors, labels = dimnames(data)[[2]], 
        CEX = 1, gap = 0.2, …)clPairsLegend(x, y, class, col, pch, …)
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.
A numeric or character vector representing a classification of observations
   (rows) of data.
Either an integer or character vector assigning a plotting symbol to each
    unique class in classification. Elements in symbols
    correspond to classes in order of appearance in the sequence of
    observations (the order used by the function unique). 
    The default is given by mclust.options("classPlotSymbols").
Either an integer or character vector assigning a color to each
    unique class in classification. Elements in colors
    correspond to classes in order of appearance in the sequence of
    observations (the order used by the function unique). 
    The default is given by mclust.options("classPlotColors").
A vector of character strings for labeling the variables. The default
    is to use the column dimension names of data.
An argument specifying the size of the plotting symbols. The default value is 1.
An argument specifying the distance between subplots (see pairs).
The x and y co-ordinates with respect to a graphic device having 
    plotting region coordinates par("usr" = c(0,1,0,1)).
The class labels.
The colors and plotting symbols appearing in the legend.
The function clPairs invisibly returns a list with the following 
  components:
A character vector of class labels.
A vector of colors used for each class.
A vector of plotting symbols used for each class.
The function clPairs draws scatter plots on the current graphics 
  device for each combination of variables in data. Observations of 
  different classifications are labeled with different symbols.
The function clPairsLegend can be used to add a legend. See examples
  below.
C. Fraley, A. E. Raftery, T. B. Murphy and L. Scrucca (2012). mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Technical Report No. 597, Department of Statistics, University of Washington.
# NOT RUN {
clPairs(iris[,1:4], cl = iris$Species)
clp <- clPairs(iris[,1:4], cl = iris$Species, lower.panel = NULL)
clPairsLegend(0.1, 0.4, class = clp$class, 
              col = clp$col, pch = clp$pch, 
              title = "Iris data")
# }
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