A quantitative Heppes Theorem and multivariate Bernoulli distributions
Resumen:
Using some extensions of a theorem of Heppes on finitely supported discrete probability measures, we address the problems of classification and testing based on projections. In particular, when the support of the distributions is known in advance (as for instance for multivariate Bernoulli distributions), a single suitably chosen projection determines the distribution. Several applications of these results are considered.
2023 | |
ANII: FCE_1_2019_1_156054 | |
Classification Discrete tomography Heppes theorem Multivariate Bernoulli Random projections Testing hypothesis |
|
Inglés | |
Universidad de la República | |
COLIBRI | |
https://hdl.handle.net/20.500.12008/37379 | |
Acceso abierto | |
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
Resultados similares
-
A classification theorem for compact Cauchy horizons in vacuum spacetimes
Autor(es):: Bustamante, Ignacio
Fecha de publicación:: (2020) -
Stable Bernoulli diffeomorphisms in dimension three
Autor(es):: Núñez, Gabriel
Fecha de publicación:: (2018) -
Distribución Bernoulli Multivariada. Una aplicación a la salud oral
Autor(es):: Álvarez-Vaz, Ramón
Fecha de publicación:: (2014) -
Central Limit Theorem for the volume of the zero set of Kostlan-Shub-Smale random polynomial systems
Autor(es):: Azaïs, J.M.
Fecha de publicación:: (2021) -
A nation-wide wi-fi RSSI dataset : Statistical analysis and resulting insights.
Autor(es):: Capdehourat, Germán
Fecha de publicación:: (2020)