Computable aggregations of random variables

Aggregation theory is devoted to the fusing of several values into a unique output that summarizes the given information. Typically, the aggregation process is formalized in terms of an increasing mathematical function that maps the input values to the result, fulfilling some boundary conditions. Ho...

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Detalles Bibliográficos
Autores: Baz, Juan, Díaz, Irene, Garmendia Salvador, Luis, Gómez González, Daniel, Magdalena, Luis, Montes, Susana
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/104589
Acceso en línea:https://hdl.handle.net/20.500.14352/104589
Access Level:acceso abierto
Palabra clave:Aggregation functions
Computable aggregations
Aggregation of random variables
Probability theory
Soft Computing
Ciencias
12 Matemáticas
11 Lógica
1208 Probabilidad
1209.03 Análisis de Datos
Descripción
Sumario:Aggregation theory is devoted to the fusing of several values into a unique output that summarizes the given information. Typically, the aggregation process is formalized in terms of an increasing mathematical function that maps the input values to the result, fulfilling some boundary conditions. However, this formalization can be too restrictive for some scenarios. In some cases, the inputs can be seen as observations of random variables, the aggregation result being also a random variable. In others, the aggregation process can be identified as a program that performs the aggregation rather than a mathematical function. In this direction, the concepts of aggregation of random variables and computable aggregation have been defined in the literature. This paper is devoted to the definition of computable aggregation of random variables, which are computer programs, not functions, that aggregate random variables, not numbers. Special attention is given to different possible alternatives to modelize random variables and monotonicity. The implementation of some examples is also provided.