R: Quantifying Similarity of Datasets and Multivariate Two- And k-Sample Testing

# Quantifying Similarity of Datasets and Multivariate Two- And k-Sample Testing

## Documentation for package ‘DataSimilarity’ version 0.4.0

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

DataSimilarity-package | Quantifying Similarity of Datasets and Multivariate Two- And k-Sample Testing
AUC | Univariate Two-Sample Statistics for DiProPerm Test
Bahr | Bahr (1996) Multivariate Two-sample Test
BallDivergence | Ball Divergence Based Two- or k-sample Test
BF | Baringhaus and Franz (2010) Rigid Motion Invariant Multivariate Two-sample Test
BG | Biau and Gyorfi (2005) Two-sample Homogeneity Test
BG2 | Biswas and Ghosh (2014) Two-Sample Test
BMG | Biswas et al. (2014) Two-sample Runs Test
BQS | Barakat et al. (1996) Two-Sample Test
C2ST | Classifier Two-Sample Test
CCS | Weighted Edge-Count Two-Sample Test
CCS_cat | Weighted Edge-Count Two-Sample Test for Discrete Data
CF | Generalized Edge-Count Test
CF_cat | Generalized Edge-Count Test for Discrete Data
CMDistance | Constrained Minimum Distance
Cramer | Cramér Two-Sample Test
DataSimilarity | Dataset Similarity
dipro.fun | Direction-Projection Functions for DiProPerm Test
DiProPerm | Direction-Projection-Permutation (DiProPerm) Test
DISCOB | Distance Components (DISCO) Tests
DISCOF | Distance Components (DISCO) Tests
DS | Rank-Based Energy Test (Deb and Sen, 2021)
dwdProj | Direction-Projection Functions for DiProPerm Test
Energy | Energy Statistic and Test
engineerMetric | Engineer Metric
f.a | Decision-Tree Based Measure of Dataset Distance and Two-Sample Test
f.aCat | Decision-Tree Based Measure of Dataset Distance and Two-Sample Test
f.s | Decision-Tree Based Measure of Dataset Distance and Two-Sample Test
f.sCat | Decision-Tree Based Measure of Dataset Distance and Two-Sample Test
findSigma | Generalized Permutation-Based Kernel (GPK) Two-Sample Test
findSimilarityMethod | Selection of Appropriate Methods for Quantifying the Similarity of Datasets
FR | Friedman-Rafsky Test
FR_cat | Friedman-Rafsky Test for Discrete Data
FStest | Multisample FS Test
GGRL | Decision-Tree Based Measure of Dataset Distance and Two-Sample Test
GGRLCat | Decision-Tree Based Measure of Dataset Distance and Two-Sample Test
GPK | Generalized Permutation-Based Kernel (GPK) Two-Sample Test
gTests | Graph-Based Tests
gTestsMulti | Graph-Based Multi-Sample Test
gTests_cat | Graph-Based Tests for Discrete Data
HamiltonPath | Shortest Hamilton path
hammingDist | Optimal Transport Dataset Distance
HMN | Random Forest Based Two-Sample Test
Jeffreys | Jeffreys Divergence
kerTests | Generalized Permutation-Based Kernel (GPK) Two-Sample Test
KMD | Kernel Measure of Multi-Sample Dissimilarity (KMD)
knn | K-Nearest Neighbor Graph
knn.bf | K-Nearest Neighbor Graph
knn.fast | K-Nearest Neighbor Graph
LHZ | Empirical Characteristic Distance
LHZStatistic | Calculation of the Li et al. (2022) Empirical Characteristic Distance
MD | Univariate Two-Sample Statistics for DiProPerm Test
method.table | List of Methods Included in the Package
MMCM | Multisample Mahalanobis Crossmatch (MMCM) Test
MMD | Maximum Mean Discrepancy (MMD) Test
MST | Minimum Spanning Tree (MST)
MST5 | Minimum Spanning Tree (MST)
MW | Nonparametric Graph-Based LP (GLP) Test
NKT | Decision-Tree Based Measure of Dataset Similarity ('Ntoutsi et al., 2008')
OTDD | Optimal Transport Dataset Distance
Petrie | Multisample Crossmatch (MCM) Test
rectPartition | Calculate a Rectangular Partition
RISE | Rank In Similarity Graph Edge-count two-sample test (RISE)
RItest | Multisample RI Test
Rosenbaum | Rosenbaum Crossmatch Test
SC | Graph-Based Multi-Sample Test
SH | Schilling-Henze Nearest Neighbor Test
stat.fun | Univariate Two-Sample Statistics for DiProPerm Test
svmProj | Direction-Projection Functions for DiProPerm Test
tStat | Univariate Two-Sample Statistics for DiProPerm Test
Wasserstein | Wasserstein Distance Based Test
YMRZL | Yu et al. (2007) Two-Sample Test
ZC | Maxtype Edge-Count Test
ZC_cat | Maxtype Edge-Count Test for Discrete Data