CorGroups: Correlation Matrix for Sub-groups

Description

The correlation matrix for sub-groups of data is computed and displayed in a graphic.

Usage

CorGroups(dat, grouping, labels1, labels2, legend, ndigits = 4,
method = "pearson", ...)

Arguments

dat

data values (probably log10-transformed)

grouping

factor with levels for different groups

labels1, labels2

labels for groups

legend

plotting legend

ndigits

number of digits to be used for plotting the numbers

method

correlation method: "pearson", "spearman" or "kendall"

…

will not be used in the function

Value

Graphic with the different sub-groups.

Details

The corralation is estimated with a non robust method but it is possible to select between the method of Pearson, Spearman and Kendall. The groups must be provided by the user.

References

C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.

Examples

Run this code

# NOT RUN {
data(chorizon)
x=chorizon[,c("Ca","Cu","Mg","Na","P","Sr","Zn")]

#definition of the groups
lit=chorizon[,"LITO"]
litolog=rep(NA, length(lit))
litolog[lit==10] <- 1
litolog[lit==52] <- 2
litolog[lit==81 | lit==82 | lit==83] <- 3
litolog[lit==7] <- 4
litolog <- litolog[!is.na(litolog)]
litolog <- factor(litolog, labels=c("AB","PG","AR","LPS"))

par(mfrow=c(1,1),mar=c(0.1,0.1,0.1,0.1))
CorGroups(log10(x), grouping=litolog, labels1=dimnames(x)[[2]],labels2=dimnames(x)[[2]],
legend=c("Caledonian Sediments","Basalts","Alkaline Rocks","Granites"),ndigits=2)

# }

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