Statistical Analysis for Environmental Data
Adaptive reweighted estimator for multivariate location and scatter
Boxes
Boxplotlegend
Boxplotlog
Boxplot based on percentiles
Bubbleplot due to Finnish method
Plot Concentration Area
Concentration Area Plot for Kola data example
Correlation Matrix
Compares Correlation Matrices
Correlation Matrix for Sub-groups
Plot Ellipses
EDA-plot for data
Edaplot for logtransformed data
Fit a Factor Analysis
Krige
Plot the Loadings of a FA
Northarrow
Principal Factor Analysis
Kola background Plot
Plot Elements of a Discriminant Analysis
Plot Ellipse
Multivariate outlier plot
Multivariate outlier plot for each dimension
Coordinates of Points Inside a Polygon
Connect the Values with a Polygon
PP plot
QP plot
QQ plot
Plot a Boxplot
Non-robust Multivariate Data Analysis
Robust Multivariate Allocation Procedure
Remove NA
Robust Multivariate Analysis
Calculate Weighted Sums for a Matrix
Compares the Robust Estimation with the Classical
Roundpretty
Subfunction for Roundpretty
Scalebar
3D plot of a Regression Model
Plots Smoothing Maps and a Legend
Internal StatDA objects
Plot Suns
Plot Legend
Ternary plot
Variance Components
Statistical analysis methods for environmental data are implemented. There is a particular focus on robust methods, and on methods for compositional data. In addition, larger data sets from geochemistry are provided. The statistical methods are described in Reimann, Filzmoser, Garrett, Dutter (2008, ISBN:978-0-470-98581-6).