Package: ddalpha 1.3.16

ddalpha: Depth-Based Classification and Calculation of Data Depth

Contains procedures for depth-based supervised learning, which are entirely non-parametric, in particular the DDalpha-procedure (Lange, Mosler and Mozharovskyi, 2014 <doi:10.1007/s00362-012-0488-4>). 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. (Pokotylo, Mozharovskyi and Dyckerhoff, 2019 <doi:10.18637/jss.v091.i05>).

Authors:Oleksii Pokotylo [aut, cre], Pavlo Mozharovskyi [aut], Rainer Dyckerhoff [aut], Stanislav Nagy [aut]

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ddalpha.pdf |ddalpha.html
ddalpha/json (API)

# Install 'ddalpha' in R:
install.packages('ddalpha', repos = c('https://pokotylo.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.79 score 2 stars 7 packages 214 scripts 3.4k downloads 76 exports 13 dependencies

Last updated 2 months agofrom:36b14b5716. Checks:OK: 3 NOTE: 6. Indexed: yes.

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Doc / VignettesOKNov 18 2024
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Exports:Cmetriccompclassf.classifycompclassf.traindatafdataf.geneexpdataf.growthdataf.medfliesdataf.populationdataf.population2010dataf.sim.1.CFF07dataf.sim.2.CFF07dataf.tecatordataf2rawfdddalpha.classifyddalpha.getErrorRateCVddalpha.getErrorRatePartddalpha.testddalpha.trainddalphaf.classifyddalphaf.getErrorRateCVddalphaf.getErrorRatePartddalphaf.testddalphaf.traindepth.depth.betaSkeletondepth.contoursdepth.contours.ddalphadepth.graphdepth.halfspacedepth.L2depth.Mahalanobisdepth.potentialdepth.projectiondepth.qhpeelingdepth.sampledepth.simplicialdepth.simplicialVolumedepth.space.depth.space.halfspacedepth.space.Mahalanobisdepth.space.potentialdepth.space.projectiondepth.space.simplicialdepth.space.simplicialVolumedepth.space.spatialdepth.space.zonoiddepth.spatialdepth.zonoiddepthf.depthf.ABDdepthf.BDdepthf.fd1depthf.fd2depthf.hMdepthf.hM2depthf.HRdepthf.RP1depthf.RP2depthf.simplicialBandderivatives.estdknn.classifydknn.classify.traineddknn.traindraw.ddplotFKSgetdatainfimalRankis.in.convexL2metriclines.functionalplot.functionalpoints.functionalrawfd2datafresetParshape.fd.analysisshape.fd.outliers

Dependencies:abindBHclassDEoptimRgeometrylinproglpSolvemagicMASSRcppRcppProgressrobustbasesfsmisc

Readme and manuals

Help Manual

Help pageTopics
Depth-Based Classification and Calculation of Data Depthddalpha-package ddalpha
Fast Computation of the Uniform Metric for Sets of Functional DataCmetric
Classify using Functional Componentwise Classifiercompclassf.classify predict.compclassf
Functional Componentwise Classifiercompclassf.train
Using Custom Depth Functions and ClassifiersCustom Methods
Converts data from fdata class to the functional class.dataf
Functional Data Sets
Gene Expression Profile Datadataf.geneexp geneexp
Berkeley Growth Study Datadataf.growth growth
Relationship of Age Patterns of Fecundity to Mortality for Female Medflies.dataf.medflies medflies
World Historical Population-by-Country Datasetdataf.population population
World Historical Population-by-Country Dataset (2010 Revision)dataf.population2010 population2010
Model 1 from Cuevas et al. (2007)dataf.sim.1.CFF07
Model 2 from Cuevas et al. (2007)dataf.sim.2.CFF07
Functional Data Set Spectrometric Data (Tecator)dataf.tecator tecator
Transform a 'dataf' Object to Raw Functional Datadataf2rawfd
Classify using DD-Classifierddalpha.classify predict.ddalpha
Test DD-Classifierddalpha.getErrorRateCV
Test DD-Classifierddalpha.getErrorRatePart
Test DD-Classifierddalpha.test
Train DD-Classifieralpha ddalpha.train knnlm maxD outsiders polynomial
Classify using Functional DD-Classifierddalphaf.classify predict.ddalphaf
Test Functional DD-Classifierddalphaf.getErrorRateCV
Test Functional DD-Classifierddalphaf.getErrorRatePart
Test Functional DD-Classifierddalphaf.test
Functional DD-Classifierddalphaf.train
Calculate Depth
Calculate Beta-Skeleton Depthdepth.betaSkeleton
Depth Contoursdepth.contours
Depth Contoursdepth.contours.ddalpha
Depth Graphdepth.graph
Calculate Halfspace Depthdepth.halfspace
Calculate L2-Depthdepth.L2
Calculate Mahalanobis Depthdepth.Mahalanobis
Calculate Potential of the Datadepth.potential
Calculate Projection Depthdepth.projection
Calculate Convex Hull Peeling Depthdepth.qhpeeling
Fast Depth Computation for Univariate and Bivariate Random Samplesdepth.sample
Calculate Simplicial Depthdepth.simplicial
Calculate Simplicial Volume Depthdepth.simplicialVolume
Calculate Depth Space using the Given Depth
Calculate Depth Space using Halfspace Depthdepth.space.halfspace
Calculate Depth Space using Mahalanobis Depthdepth.space.Mahalanobis
Calculate Potential Spacedepth.space.potential
Calculate Depth Space using Projection Depthdepth.space.projection
Calculate Depth Space using Simplicial Depthdepth.space.simplicial
Calculate Depth Space using Simplicial Volume Depthdepth.space.simplicialVolume
Calculate Depth Space using Spatial Depthdepth.space.spatial
Calculate Depth Space using Zonoid Depthdepth.space.zonoid
Calculate Spatial Depthdepth.spatial
Calculate Zonoid Depthdepth.zonoid
Calculate Functional Depth
Adjusted Band Depth for Functional Datadepthf.ABD
Band Depth for Functional Datadepthf.BD
Univariate Integrated and Infimal Depth for Functional Datadepthf.fd1
Bivariate Integrated and Infimal Depth for Functional Datadepthf.fd2
h-Mode Depth for Functional Datadepthf.hM
Bivariate h-Mode Depth for Functional Data Based on the L^2 Metricdepthf.hM2
Half-Region Depth for Functional Datadepthf.HR
Univariate Random Projection Depths for Functional Datadepthf.RP1
Bivariate Random Projection Depths for Functional Datadepthf.RP2
Calculate Simplicial Band Depthdepthf.simplicialBand
Estimation of the First Two Derivatives for Functional Dataderivatives.est
Depth-Based kNNdknn.classify
Depth-Based kNNdknn.classify.trained
Depth-Based kNNdknn.train
Draw _DD_-Plotdraw.ddplot
Fast Kernel SmoothingFKS
Data for Classificationbaby banknoten biomed bloodtransfusion breast_cancer_wisconsin bupa chemdiab_1vs2 chemdiab_1vs3 chemdiab_2vs3 cloud crabB_MvsF crabF_BvsO crabM_BvsO crabO_MvsF crab_BvsO crab_MvsF cricket_CvsP data diabetes ecoli_cpvsim ecoli_cpvspp ecoli_imvspp gemsen_MvsF getdata glass groessen_MvsF haberman heart hemophilia indian_liver_patient_1vs2 indian_liver_patient_FvsM irish_ed_MvsF iris_setosavsversicolor iris_setosavsvirginica iris_versicolorvsvirginica kidney pima plasma_retinol_MvsF segmentation socmob_IvsNI socmob_WvsB tae tennis_MvsF tips_DvsN tips_MvsF uscrime_SvsN vertebral_column veteran_lung_cancer vowel_MvsF wine_1vs2 wine_1vs3 wine_2vs3
Adjusted Ranking of Functional Data Based on the Infimal DepthinfimalRank
Check Outsidernessis.in.convex
Fast Computation of the L^2 Metric for Sets of Functional DataL2metric
Plots for the "ddalpha" Classplot.ddalpha
Plots for the "ddalphaf" Classplot.ddalphaf
Plot functions for the Functional Datalines.functional plot.functional points.functional
Transform Raw Functional Data to a 'dataf' Objectrawfd2dataf
Reset Graphical ParametersresetPar
Diagnostic Plot for First and Second Order Integrated and Infimal Depthsshape.fd.analysis
Functional Depth-Based Shape Outlier Detectionshape.fd.outliers