PCAcoda: Principal Analysis Components using the Compositional Data...

In AdrianaPina/HydroCODA: Multistatical analysis using the compositional data approach for hydrochemical water samples

Principal Analysis Components using the Compositional Data (CoDA) approach.

Description

Principal Analysis Components using the Compositional Data (CoDA) approach for the data treatment and the Centered log ratio - clr transformation (Aitchison, 1982).

Usage

PCAcoda(Dataclust, comp1, comp2)

Arguments

Dataclust	is a matrix that contains the hydrochemical composition of water samples and the assigned cluster using the waterclust function. Titles must be as follows: ID, long, lat, source, Mg, Ca, Na, K, HCO3, Cl,SO4, NO3, NO2, Fe. All concentrations are in meq/l. Aditional chemical compounds must be added in columns after the Fe column concentration.
comp1	is a numeric value indicating the number of the component to be plotted on the x-axys.
comp2	is a numeric value indicating the number of the component to be plotted on the y-axys.

Value

returns an interactive compositional biplot with the selected compositions, the samples description and the assigned cluster from the waterclust function; a summary of the PCA analysis with the Standard deviation, the Proportion of Variance and the Cumulative Proportion for each composition; a list with class "princomp" (see compositions documentation)

a list that comprises a figure and two dataframes. The figure is an interactive compositional biplot with the selected compositions, the samples description and the assigned cluster from the waterclust function; The first list, is the summary of the PCA analysis with the Standard deviation, the Proportion of Variance and the Cumulative Proportionfor each composition. The second one is a list with class "princomp" (see compositions documentation).

Author(s)

Adriana Piña [e-mail]
David Zamora [e-mail]

References

Aitchison, J. (1982). The Statistical Analysis of Compositional Data. Journal of the Royal Statistical Society. Series B (Methodological), 44(2), 139–177.

Examples

data("Balance")
Dataclust <- waterclust(Balance, height = 50, typ = 2, chem.name = FALSE)
PCAcoda(Dataclust, comp1 = 1, comp2 = 2)

AdrianaPina/HydroCODA documentation built on Feb. 1, 2023, 5:43 a.m.