Package: bigmds Title: Multidimensional Scaling for Big Data Version: 3.0.0 Authors@R: c(person(given = "Cristian", family = "Pachón García", role = c("aut", "cre"), email = "cc.pachon@gmail.com", comment = c(ORCID = "0000-0001-9518-4874")), person(given = "Pedro", family = "Delicado", role = c("aut"), email = "pedro.delicado@upc.edu", comment = c(ORCID = "0000-0003-3933-4852"))) Description: MDS is a statistic tool for reduction of dimensionality, using as input a distance matrix of dimensions n × n. When n is large, classical algorithms suffer from computational problems and MDS configuration can not be obtained. With this package, we address these problems by means of six algorithms, being two of them original proposals: - Landmark MDS proposed by De Silva V. and JB. Tenenbaum (2004). - Interpolation MDS proposed by Delicado P. and C. Pachón-García (2021) (original proposal). - Reduced MDS proposed by Paradis E (2018). - Pivot MDS proposed by Brandes U. and C. Pich (2007) - Divide-and-conquer MDS proposed by Delicado P. and C. Pachón-García (2021) (original proposal). - Fast MDS, proposed by Yang, T., J. Liu, L. McMillan and W. Wang (2006). License: MIT + file LICENSE Encoding: UTF-8 Roxygen: list(markdown = TRUE) RoxygenNote: 7.2.3 Depends: R (>= 3.0.2) Suggests: testthat Imports: pracma, svd, corpcor, parallel, stats URL: https://github.com/pachoning/bigmds BugReports: https://github.com/pachoning/bigmds/issues Repository: https://pachoning.r-universe.dev Date/Publication: 2024-01-09 14:51:17 UTC RemoteUrl: https://github.com/pachoning/bigmds RemoteRef: HEAD RemoteSha: 26c5739325d0ada177e4a0e216bf599b70f49ce7 NeedsCompilation: no Packaged: 2026-10-08 09:30:20 UTC; root Author: Cristian Pachón García [aut, cre] (ORCID: ), Pedro Delicado [aut] (ORCID: ) Maintainer: Cristian Pachón García