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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Aaron, Catherine | es |
dc.contributor.author | Cholaquidis, Alejandro | es |
dc.contributor.author | Cuevas, A. | es |
dc.date.accessioned | 2019-10-02T22:14:51Z | - |
dc.date.available | 2019-10-02T22:14:51Z | - |
dc.date.issued | 2017 | es |
dc.date.submitted | 20191001 | es |
dc.identifier.citation | Aaron, C.,Cholaquidis, A., Cuevas, A.Detection of low dimensionality and data denoising via set estimation techniques. Electronic Journal of Statistics, 2017, 11 (2): 4596-4628.doi: 10.1214/17-EJS1370 | es |
dc.identifier.issn | 1935-7524 | es |
dc.identifier.uri | https://hdl.handle.net/20.500.12008/22092 | - |
dc.description.abstract | This work is closely related to the theories of set estimation and manifold estimation. Our object of interest is a, possibly lower-dimensional, compact set S ⊂ ℝd. The general aim is to identify (via stochastic procedures) some qualitative or quantitative features of S, of geometric or topological character. The available information is just a random sample of points drawn on S. The term “to identify” means here to achieve a correct answer almost surely (a.s.) when the sample size tends to infinity. More specifically the paper aims at giving some partial answers to the following questions: is S full dimensional? Is S “close to a lower dimensional set” M? If so, can we estimate M or some functionals of M (in particular, the Minkowski content of M)? As an important auxiliary tool in the answers of these questions, a denoising procedure is proposed in order to partially remove the noise in the original data. The theoretical results are complemented with some simulations and graphical illustrations. © 2017, Institute of Mathematical Statistics. | es |
dc.format.mimetype | application/pdf | es |
dc.language.iso | en | es |
dc.publisher | Institute of Mathematical Statistics | es |
dc.relation.ispartof | Electronic Journal of Statistics, 2017, 11 (2): 4596-4628 | es |
dc.rights | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
dc.subject | Boundary estimation | es |
dc.subject | Denoising procedure | es |
dc.subject | Minkowski content | es |
dc.title | Detection of low dimensionality and data denoising via set estimation techniques | es |
dc.type | Artículo | es |
dc.contributor.filiacion | Cholaquidis, Alejandro. Universidad de la República (Uruguay). Facultad de Ciencias. Instituto de Matemática | es |
dc.rights.licence | Licencia Creative Commons Atribución (CC –BY 4.0) | es |
dc.identifier.doi | 10.1214/17-EJS1370 | es |
Aparece en las colecciones: | Publicaciones académicas y científicas - Facultad de Ciencias |
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10121417EJS1370.pdf | 7,58 MB | Adobe PDF | Visualizar/Abrir |
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