The Kernel Estimation in Biosystems Engineering.

Ayuga Téllez, Esperanza and Grande Ortiz, M. Angeles and González García, Concepción and Martín Fernández, Ángel Julián and 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.

Description

Title: The Kernel Estimation in Biosystems Engineering.
Author/s:
  • Ayuga Téllez, Esperanza
  • Grande Ortiz, M. Angeles
  • González García, Concepción
  • Martín Fernández, Ángel Julián
  • García García, Ana Isabel
Item Type: Article
Título de Revista/Publicación: Journal of Systemics, Cybernetics and Informatics
Date: January 2008
ISSN: 1690-4524
Volume: 6
Subjects:
Faculty: E.T.S.I. Montes (UPM)
Department: Economía y Gestión Forestal [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (158kB) | Preview

Abstract

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.

More information

Item ID: 2155
DC Identifier: http://oa.upm.es/2155/
OAI Identifier: oai:oa.upm.es:2155
Official URL: http://www.iiisci.org/Journal/sci/Contents.asp?var=&Previous=ISS0902
Deposited by: Memoria Investigacion
Deposited on: 01 Feb 2010 08:51
Last Modified: 20 Apr 2016 11:54
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM