acg |
Angular Central Gaussian Distribution |
cities |
Data : Populated Cities in the U.S. |
dacg |
Angular Central Gaussian Distribution |
density |
S3 method for mixture model : evaluate density |
density.moSL |
Finite Mixture of Spherical Laplace Distributions |
density.moSN |
Finite Mixture of Spherical Normal Distributions |
dmacg |
Matrix Angular Central Gaussian Distribution |
dsplaplace |
Spherical Laplace Distribution |
dspnorm |
Spherical Normal Distribution |
ERP |
Data : EEG Covariances for Event-Related Potentials |
gorilla |
Data : Gorilla Skull |
grassmann.optmacg |
Estimation of Distribution Algorithm with MACG Distribution |
grassmann.runif |
Generate Uniform Samples on Grassmann Manifold |
grassmann.utest |
Test of Uniformity on Grassmann Manifold |
hands |
Data : Left Hands |
label |
S3 method for mixture model : predict labels |
label.moSL |
Finite Mixture of Spherical Laplace Distributions |
label.moSN |
Finite Mixture of Spherical Normal Distributions |
loglkd |
S3 method for mixture model : log-likelihood |
loglkd.moSL |
Finite Mixture of Spherical Laplace Distributions |
loglkd.moSN |
Finite Mixture of Spherical Normal Distributions |
macg |
Matrix Angular Central Gaussian Distribution |
mle.acg |
Angular Central Gaussian Distribution |
mle.macg |
Matrix Angular Central Gaussian Distribution |
mle.splaplace |
Spherical Laplace Distribution |
mle.spnorm |
Spherical Normal Distribution |
moSL |
Finite Mixture of Spherical Laplace Distributions |
moSN |
Finite Mixture of Spherical Normal Distributions |
orbital |
Data : Normal Vectors to the Orbital Planes of the 9 Planets |
passiflora |
Data : Passiflora Leaves |
predict.m2skreg |
Prediction for Manifold-to-Scalar Kernel Regression |
racg |
Angular Central Gaussian Distribution |
riem.clrq |
Competitive Learning Riemannian Quantization |
riem.coreset18B |
Build Lightweight Coreset |
riem.distlp |
Distance between Two Curves on Manifolds |
riem.dtw |
Dynamic Time Warping Distance |
riem.fanova |
Fréchet Analysis of Variance |
riem.fanovaP |
Fréchet Analysis of Variance |
riem.hclust |
Hierarchical Agglomerative Clustering |
riem.interp |
Geodesic Interpolation |
riem.interps |
Geodesic Interpolation of Multiple Points |
riem.isomap |
Isometric Feature Mapping |
riem.kmeans |
K-Means Clustering |
riem.kmeans18B |
K-Means Clustering with Lightweight Coreset |
riem.kmeanspp |
K-Means++ Clustering |
riem.kmedoids |
K-Medoids Clustering |
riem.knn |
Find K-Nearest Neighbors |
riem.kpca |
Kernel Principal Component Analysis |
riem.m2skreg |
Manifold-to-Scalar Kernel Regression |
riem.m2skregCV |
Manifold-to-Scalar Kernel Regression with K-Fold Cross Validation |
riem.mds |
Multidimensional Scaling |
riem.mean |
Fréchet Mean and Variation |
riem.median |
Fréchet Median and Variation |
riem.nmshift |
Nonlinear Mean Shift |
riem.pdist |
Compute Pairwise Distances for Data |
riem.pdist2 |
Compute Pairwise Distances for Two Sets of Data |
riem.pga |
Principal Geodesic Analysis |
riem.phate |
PHATE |
riem.rmml |
Riemannian Manifold Metric Learning |
riem.sammon |
Sammon Mapping |
riem.sc05Z |
Spectral Clustering by Zelnik-Manor and Perona (2005) |
riem.scNJW |
Spectral Clustering by Ng, Jordan, and Weiss (2002) |
riem.scSM |
Spectral Clustering by Shi and Malik (2000) |
riem.scUL |
Spectral Clustering with Unnormalized Laplacian |
riem.seb |
Find the Smallest Enclosing Ball |
riem.test2bg14 |
Two-Sample Test modified from Biswas and Ghosh (2014) |
riem.test2wass |
Two-Sample Test with Wasserstein Metric |
riem.tsne |
t-distributed Stochastic Neighbor Embedding |
riem.wasserstein |
Wasserstein Distance between Empirical Measures |
rmacg |
Matrix Angular Central Gaussian Distribution |
rmvnorm |
Generate Random Samples from Multivariate Normal Distribution |
rsplaplace |
Spherical Laplace Distribution |
rspnorm |
Spherical Normal Distribution |
spd.geometry |
Supported Geometries on SPD Manifold |
spd.pdist |
Pairwise Distance on SPD Manifold |
spd.wassbary |
Wasserstein Barycenter of SPD Matrices |
sphere.convert |
Convert between Cartesian Coordinates and Geographic Coordinates |
sphere.geo2xyz |
Convert between Cartesian Coordinates and Geographic Coordinates |
sphere.runif |
Generate Uniform Samples on Sphere |
sphere.utest |
Test of Uniformity on Sphere |
sphere.xyz2geo |
Convert between Cartesian Coordinates and Geographic Coordinates |
splaplace |
Spherical Laplace Distribution |
spnorm |
Spherical Normal Distribution |
stiefel.optSA |
Simulated Annealing on Stiefel Manifold |
stiefel.runif |
Generate Uniform Samples on Stiefel Manifold |
stiefel.utest |
Test of Uniformity on Stiefel Manifold |
wrap.correlation |
Prepare Data on Correlation Manifold |
wrap.euclidean |
Prepare Data on Euclidean Space |
wrap.grassmann |
Prepare Data on Grassmann Manifold |
wrap.landmark |
Wrap Landmark Data on Shape Space |
wrap.multinomial |
Prepare Data on Multinomial Manifold |
wrap.rotation |
Prepare Data on Rotation Group |
wrap.spd |
Prepare Data on Symmetric Positive-Definite (SPD) Manifold |
wrap.spdk |
Prepare Data on SPD Manifold of Fixed-Rank |
wrap.sphere |
Prepare Data on Sphere |
wrap.stiefel |
Prepare Data on (Compact) Stiefel Manifold |