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Riemann  

Learning with Data on Riemannian Manifolds
View on CRAN: Click here


Download and install Riemann package within the R console
Install from CRAN:
install.packages("Riemann")

Install from Github:
library("remotes")
install_github("cran/Riemann")

Install by package version:
library("remotes")
install_version("Riemann", "0.1.4")



Attach the package and use:
library("Riemann")
Maintained by
Kisung You
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-22
Latest Update: 2022-02-28
Description:
We provide a variety of algorithms for manifold-valued data, including Fréchet summaries, hypothesis testing, clustering, visualization, and other learning tasks. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> for general exposition to statistics on manifolds.
How to cite:
Kisung You (2020). Riemann: Learning with Data on Riemannian Manifolds. R package version 0.1.4, https://cran.r-project.org/web/packages/Riemann
Previous versions and publish date:
0.1.0 (2020-09-22 11:40), 0.1.1 (2021-05-05 18:00), 0.1.3 (2021-06-20 11:50)
Other packages that cited Riemann R package
View Riemann citation profile
Other R packages that Riemann depends, imports, suggests or enhances
Functions, R codes and Examples using the Riemann R package
Some associated functions: ERP . acg . cities . density . gorilla . grassmann.optmacg . grassmann.runif . grassmann.utest . hands . label . loglkd . macg . moSL . moSN . orbital . passiflora . predict.m2skreg . riem.clrq . riem.coreset18B . riem.distlp . riem.dtw . riem.fanova . riem.hclust . riem.interp . riem.interps . riem.isomap . riem.kmeans . riem.kmeans18B . riem.kmeanspp . riem.kmedoids . riem.knn . riem.kpca . riem.m2skreg . riem.m2skregCV . riem.mds . riem.mean . riem.median . riem.nmshift . riem.pdist . riem.pdist2 . riem.pga . riem.phate . riem.rmml . riem.sammon . riem.sc05Z . riem.scNJW . riem.scSM . riem.scUL . riem.seb . riem.test2bg14 . riem.test2wass . riem.tsne . riem.wasserstein . rmvnorm . spd.geometry . spd.pdist . spd.wassbary . sphere.convert . sphere.runif . sphere.utest . splaplace . spnorm . stiefel.optSA . stiefel.runif . stiefel.utest . wrap.correlation . wrap.euclidean . wrap.grassmann . wrap.landmark . wrap.multinomial . wrap.rotation . wrap.spd . wrap.spdk . wrap.sphere . wrap.stiefel . 
Some associated R codes: RcppExports.R . auxiliary_checkers.R . auxiliary_others.R . auxiliary_ported.R . basic_interp.R . basic_interps.R . basic_pdist.R . basic_pdist2.R . basic_wasserstein.R . clustering_clrq.R . clustering_hclust.R . clustering_kmeans.R . clustering_kmeans18B.R . clustering_kmeanspp.R . clustering_kmedoids.R . clustering_nmshift.R . clustering_sc05Z.R . clustering_scNJW.R . clustering_scSM.R . clustering_scUL.R . curve_distlp.R . curve_dtw.R . data_ERP.R . data_cities.R . data_gorilla.R . data_hands.R . data_orbital.R . data_passiflora.R . dist_acg.R . dist_macg.R . dist_splaplace.R . dist_spnorm.R . future_clustering_critint.R . future_clustering_rsup.R . future_dist_vmf.R . inference_fanova.R . inference_m2skreg.R . inference_m2skregCV.R . inference_mean.R . inference_median.R . inference_test2bg14.R . inference_test2wass.R . learning_coreset18B.R . learning_knn.R . learning_rmml.R . learning_seb.R . mixture_methods.R . mixture_sphere_SL.R . mixture_sphere_SN.R . package-Riemann.R . special_grassmann_optmacg.R . special_grassmann_runif.R . special_grassmann_utest.R . special_spd_geometry.R . special_spd_pdist.R . special_spd_wassbary.R . special_sphere.R . special_stiefel.R . utility_rmvnorm.R . visualization_isomap.R . visualization_kpca.R . visualization_mds.R . visualization_pga.R . visualization_phate.R . visualization_sammon.R . visualization_tsne.R . wrap01sphere.R . wrap02spd.R . wrap03correlation.R . wrap04stiefel.R . wrap05grassmann.R . wrap06rotation.R . wrap07multinomial.R . wrap08spdk.R . wrap10euclidean.R . wrap12landmark.R . zzz.R .  Full Riemann package functions and examples
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