correlationCoefPlot {GCDkit}R Documentation

Statistics: Correlation coefficient patterns

Description

Produces set of plots of correlation coefficient patterns, for the entire dataset or separately for each group.

Usage

correlationCoefPlot(elems = NULL, groups = NULL, method = "pearson", 
    use = "pairwise.complete.obs")

Arguments

elems

list of desired elements

groups

a character vector with grouping information

method

a character string indicating which correlation coefficient (or covariance) is to be computed

use

an optional character string giving a method for computing covariances in the presence of missing values

Details

This function calculates and plots correlation coefficient patterns either for the whole dataset (if 'groups = NULL') or by individual groups.

For meaning of parameters 'methods' and 'use', see cor.

The utility of pairwise correlation coefficient patterns was demonstrated by Rollinson (1993 and references therein). In principle, a similarity in correlation patterns between two or more elements means their analogous geochemical behaviour, potentially reflecting the operation of the same petrogenetic/geological process (fractional crystallization, partial melting, weathering, hydrothermal alteration...)

correlationCoefPlot.png

The variables are selected using the function 'selectColumnsLabels'.

Value

A list with the values of pairwise correlation in the whole dataset or in each of the groups.

Author(s)

Vojtěch Janoušek, vojtech.janousek@geology.cz

References

Rollinson HR (1993) Using Geochemical Data: Evaluation, Presentation, Interpretation. Longman, London, p. 1-352

See Also

cor

Examples

    data(atacazo)
    accessVar("atacazo")
    
    # The whole dataset
    correlationCoefPlot(elems="K,Rb,Ba,Sr,Cr,Ni,Zr,Nb,Ti")
    
    # By currently defined groups 
    groupsByLabel("Volcano")
    correlationCoefPlot(elems="K,Rb,Ba,Sr,Cr,Ni,Zr,Nb,Ti",groups)

[Package GCDkit version 6.1 Index]