General two sample tests base on supremum kernel distances
L. A. Rodríguez Ramírez, J. Cárcamo, A. Cuevas González
El problema de dos muestras o problema de homogeneidad es uno de los más estudiados en estadística por su interés en ciencia y tecnología. En especial, destacan por su claridad y simplicidad los tests de homogeneidad basados en distancias. En la última década, debido al creciente interés en nuevos tipos de datos (alta dimensión, FDA, datos en variedades,...) han aparecido nuevas propuestas de métricas que permiten afrontar este problema, y otros, en estos paradigmas. Un ejemplo de ello son las distancias kernel. En esta charla hablaré de estas distancias y de nuestra propuesta para mejorar sus resultados: las supremum kernel distances.
Keywords: Functional data analysis, high dimensional data, homogeneity test, two sample problem, kernel distances, supremum distances, maximum mean discrepancy, kernel trick
Scheduled
GT06 Functional Data Analysis III. Recent contributions
June 8, 2022 5:20 PM
Grade Hall
Other papers in the same session
M. Febrero-Bande, P. Galeano San Miguel, E. García Portugués, W. González-Manteiga
A. Coín, J. R. Berrendero, A. Cuevas
C. L. Urbano Leon, M. Escabias Machuca
L. Freijeiro González, M. Febrero Bande, W. González Manteiga
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