dc.creator | Solís Chacón, Maikol | |
dc.creator | Hernández Alvarado, Alberto José | |
dc.creator | Zúñiga Rojas, Ronald Alberto | |
dc.date.accessioned | 2018-12-20T15:20:45Z | |
dc.date.available | 2018-12-20T15:20:45Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | https://hdl.handle.net/10669/76360 | |
dc.description.abstract | Abstract The course of dimensionality is a common problem in statistics and data
analysis. Variable sensitivity analysis methods are a well studied and established
set of tools designed to overcome these sorts of problems. However, as this work
shows, these methods fail to capture relevant features and patterns hidden within
the geometry of the enveloping manifold projected into a variable. We propose an
index that captures, reflects and correlates the relevance of distinct variables within
a model by focusing on the geometry of their projections. The analysis was made
with an original R-package called TopSA, short for Topological Sensitivity Anal-
ysis. The TopSA R-package is available on the site https://github.com/maikol-
solis/TopSA. | es_ES |
dc.language.iso | es | es_ES |
dc.subject | Homology | es_ES |
dc.subject | Topological manifolds | es_ES |
dc.subject | Sensitivity Analysis | es_ES |
dc.subject | Simplexes | es_ES |
dc.subject | 510 Matemáticas | es_ES |
dc.title | Geometrical correlation indices using homological constructions on manifolds | es_ES |
dc.type | artículo preliminar | |
dc.description.procedence | UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones en Matemáticas Puras y Aplicadas (CIMPA) | es_ES |
dc.description.procedence | UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones en Matemática y Meta-Matemática (CIMM) | es_ES |