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 |