PCAPlot

Data frame containing source and mixtures data

data

Numeric vector containing the index of the two principal components in the chart

components

The function performs a principal components analysis on the given data matrix and displays a biplot using vqv.ggbiplot package of the results for each different source to help the user in the decision.

Quantifies the provenance of the sediments in a catchment or study area. Based on a comprehensive characterization of the sediment sources and the end sediment mixtures a mixing model algorithm is applied to the sediment mixtures in order to estimate the relative contribution of each potential source. The package includes several statistical methods such as Kruskal-Wallis test, discriminant function analysis ('DFA'), principal component plot ('PCA') to select the optimal subset of tracer properties. The variability within each sediment source is also considered to estimate the statistical distribution of the sources contribution.

Ivan Lizaga

fingerPro

PCAPlot: Principal component analysis chart

Description

Usage

Arguments