A Short Note on a Multi-Gaussian Model for Multivariate Estimation and Simulation

dc.contributor.authorRiquelme, Alvaro I.
dc.contributor.authorOrtiz, Julian M.
dc.date.accessioned2020-10-29T21:26:35Z
dc.date.available2020-10-29T21:26:35Z
dc.date.issued2020
dc.description.abstractWe show that multivariate non-linear features can be reconstructed in a simple and straightforward way by mapping the original p-variate cumulative distribution function with a p-variate Gaussian distribution, equipped with a proper prior covariance matrix. We present theoretical development that allows a proper fitting of such covariance matrix, allowing to continue with the decorrelation of variables by the use principal components analysis.en
dc.identifier.citationRiquelme, A., Ortiz JM (2020) A Short Note on a Multi-Gaussian Model for Multivariate Estimation and Simulation, paper 2020-03. Preprint.en
dc.identifier.urihttp://hdl.handle.net/1974/28551
dc.language.isoenen
dc.publisherQueen's Universityen
dc.relationQueen's University Research Initiation Granten
dc.relationMitacs Accelerateen
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleA Short Note on a Multi-Gaussian Model for Multivariate Estimation and Simulationen
dc.typepreprinten
oaire.awardNumberRGPIN-2017-04200en
oaire.awardNumberRGPAS-2017-507956en
oaire.awardNumberFR37072-IT14668en
project.funder.identifierhttp://dx.doi.org/10.13039/501100003321en
project.funder.identifierhttp://dx.doi.org//10.13039/501100000038en
project.funder.identifierhttp://dx.doi.org/10.13039/501100004489en
project.funder.nameQueen's Universityen
project.funder.nameNSERCen
project.funder.nameMitacsen
project.funder.nameSRK Consulting Canadaen
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