B. Sinova Fernández

Los datos difusos constituyen una herramienta muy útil para modelar la información imprecisa procedente de muchos experimentos aleatorios. Por ello, su presencia está creciendo en campos como la Ingeniería, Biomedicina, Psicología… y la variedad de técnicas estadísticas disponibles para su análisis es cada vez mayor. En particular, en la literatura se han adaptado diversas medidas de tendencia central: la mediana, los M-estimadores y las medias recortadas empíricas. Debido a los buenos resultados de estas últimas, interesaría abordar otras alternativas para definir las medias recortadas para datos difusos, como las basadas en profundidades. Este enfoque es habitual en el análisis de datos funcionales, por lo que, como primer acercamiento, se mostrará el comportamiento empírico de las medias recortadas que evalúan la profundidad de un dato difuso con base en su identificación con una función. En segundo lugar, se propondrá una profundidad diseñada específicamente para datos difusos.

Keywords: Datos difusos, media recortada, profundidad


GT04 Multivariate Analysis and Classification III
June 7, 2022  4:50 PM
Cloister room

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