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ddalpha (version 1.3.8)

Depth-Based Classification and Calculation of Data Depth

Description

Contains procedures for depth-based supervised learning, which are entirely non-parametric, in particular the DDalpha-procedure (Lange, Mosler and Mozharovskyi, 2014 ). The training data sample is transformed by a statistical depth function to a compact low-dimensional space, where the final classification is done. It also offers an extension to functional data and routines for calculating certain notions of statistical depth functions. 50 multivariate and 5 functional classification problems are included.

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Version

Install

install.packages('ddalpha')

Monthly Downloads

2,678

Version

1.3.8

License

GPL-2

Maintainer

Oleksii Pokotylo

Last Published

January 6th, 2019

Functions in ddalpha (1.3.8)

Berkeley Growth Study Data

dataf.population

World Historical Population-by-Country Dataset

dataf.population2010

World Historical Population-by-Country Dataset (2010 Revision)

compclassf.classify

Classify using Functional Componentwise Classifier

Calculate L2-Depth

depth.Mahalanobis

Calculate Mahalanobis Depth

Functional Data Sets

compclassf.train

Functional Componentwise Classifier

Gene Expression Profile Data

depth.projection

Calculate Projection Depth

ddalpha.getErrorRateCV

Test DD-Classifier

dataf.sim.1.CFF07

Model 1 from Cuevas et al. (2007)

dataf.sim.2.CFF07

Model 2 from Cuevas et al. (2007)

Test DD-Classifier

Fast Computation of the Uniform Metric for Sets of Functional Data

ddalphaf.classify

Classify using Functional DD-Classifier

depth.qhpeeling

Calculate Convex Hull Peeling Depth

Train DD-Classifier

ddalpha.getErrorRatePart

Test DD-Classifier

depth.space.simplicial

Calculate Depth Space using Simplicial Depth

Using Custom Depth Functions and Classifiers

depth.betaSkeleton

Calculate Beta-Skeleton Depth

ddalpha-package

Depth-Based Classification and Calculation of Data Depth

depth.space.simplicialVolume

Calculate Depth Space using Simplicial Volume Depth

ddalpha.classify

Classify using DD-Classifier

Band Depth for Functional Data

Half-Region Depth for Functional Data

Fast Kernel Smoothing

Fast Computation of the \(L^2\) Metric for Sets of Functional Data

dknn.classify.trained

Depth-Based kNN

Functional Data Set Spectrometric Data (Tecator)

Depth-Based kNN

depth.contours.ddalpha

Transform a dataf Object to Raw Functional Data

ddalphaf.getErrorRatePart

Test Functional DD-Classifier

depth.space.Mahalanobis

Calculate Depth Space using Mahalanobis Depth

depth.space.halfspace

Calculate Depth Space using Halfspace Depth

Test Functional DD-Classifier

Fast Depth Computation for Univariate and Bivariate Random Samples

Functional DD-Classifier

Calculate Spatial Depth

depth.simplicial

Calculate Simplicial Depth

ddalphaf.getErrorRateCV

Test Functional DD-Classifier

Calculate Zonoid Depth

Calculate Depth

depth.space.potential

Calculate Potential Space

h-Mode Depth for Functional Data

depth.halfspace

Calculate Halfspace Depth

Bivariate h-Mode Depth for Functional Data Based on the \(L^2\) Metric

plot.functional

Plot functions for the Functional Data

depth.potential

Calculate Potential of the Data

Univariate Random Projection Depths for Functional Data

depth.space.spatial

Calculate Depth Space using Spatial Depth

depth.simplicialVolume

Calculate Simplicial Volume Depth

Calculate Depth Space using the Given Depth

Bivariate Random Projection Depths for Functional Data

depth.space.projection

Calculate Depth Space using Projection Depth

shape.fd.outliers

Functional Depth-Based Shape Outlier Detection

Univariate Integrated and Infimal Depth for Functional Data

Calculate Functional Depth

Adjusted Band Depth for Functional Data

Transform Raw Functional Data to a dataf Object

Bivariate Integrated and Infimal Depth for Functional Data

depth.space.zonoid

Calculate Depth Space using Zonoid Depth

Adjusted Ranking of Functional Data Based on the Infimal Depth

derivatives.est

Estimation of the First Two Derivatives for Functional Data

Data for Classification

Depth-Based kNN

Check Outsiderness

Plots for the "ddalpha" Class

Reset Graphical Parameters

Plots for the "ddalphaf" Class

shape.fd.analysis

Diagnostic Plot for First and Second Order Integrated and Infimal Depths

Relationship of Age Patterns of Fecundity to Mortality for Female Medflies.