Depth Measures in Multivariate, Regression and Functional Settings
Draws a bagplot, a bivariate boxplot
Location estimates based on halfspace depth.
Adjusted outlyingness of points relative to a dataset
Bagdistance of points relative to a dataset
Test for linearity of the conditional median in simple regression
Computations for drawing a bagplot
Depth contours of multivariate data
Directional outlyingness of points relative to a dataset
distSpace
Directional projection depth of points relative to a dataset
Location estimates based on directional projection depth
Draws a heatmap of functional depth values or distances
Draws the Functional Outlier Map (FOM)
Functional outlyingness measures for functional data
Halfspace depth of points relative to a dataset
A robust measure of skewness for univariate data
Multivariate functional depth for functional data
Multivariate functional median for functional data
Rainbow plot for bivariate data
Stahel-Donoho outlyingness of points relative to a dataset
Draws depth contours of bivariate data
Projection depth of points relative to a dataset
Location estimates based on projection depth
Regression depth of hyperplanes
Hyperplane of maximal regression depth
Simplicial depth of points relative to a dataset
Skewness-adjusted projection depth of points relative to a dataset
Location estimates based on skewness-adjusted projection depth
Test for angular symmetry around a specified center for bivariate data
Tools to compute depth measures and implementations of related tasks such as outlier detection, data exploration and classification of multivariate, regression and functional data.