The Kernel Estimation in Biosystems Engineering.

Ayuga Téllez, Esperanza; Grande Ortiz, M. Angeles; González García, Concepción; Martín Fernández, Ángel Julián y García García, Ana Isabel (2008). The Kernel Estimation in Biosystems Engineering.. "Journal of Systemics, Cybernetics and Informatics", v. 6 (n. 2); pp. 23-27. ISSN 1690-4524.

Descripción

Título: The Kernel Estimation in Biosystems Engineering.
Autor/es:
  • Ayuga Téllez, Esperanza
  • Grande Ortiz, M. Angeles
  • González García, Concepción
  • Martín Fernández, Ángel Julián
  • García García, Ana Isabel
Tipo de Documento: Artículo
Título de Revista/Publicación: Journal of Systemics, Cybernetics and Informatics
Fecha: Enero 2008
Volumen: 6
Materias:
Escuela: E.T.S.I. Montes (UPM) [antigua denominación]
Departamento: Economía y Gestión Forestal [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than “a priori” assumption of the global target function shape (e.g., linear or quadratic). In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

Más información

ID de Registro: 2155
Identificador DC: http://oa.upm.es/2155/
Identificador OAI: oai:oa.upm.es:2155
URL Oficial: http://www.iiisci.org/Journal/sci/Contents.asp?var=&Previous=ISS0902
Depositado por: Memoria Investigacion
Depositado el: 01 Feb 2010 08:51
Ultima Modificación: 20 Abr 2016 11:54
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