| correlationCoefPlot {GCDkit} | R Documentation | 
Produces set of plots of correlation coefficient patterns, for the entire dataset or separately for each group.
correlationCoefPlot(elems = NULL, groups = NULL, method = "pearson", 
    use = "pairwise.complete.obs")
| 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 | 
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...)
 
 
The variables are selected using the function 'selectColumnsLabels'.
A list with the values of pairwise correlation in the whole dataset or in each of the groups.
Vojtěch Janoušek, vojtech.janousek@geology.cz
Rollinson HR (1993) Using Geochemical Data: Evaluation, Presentation, Interpretation. Longman, London, p. 1-352
    sampleDataset("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)