Model evaluation and selection in multiple nonlinear regression analysis

Autor:	Gints Jēkabsons, Jurijs Lavendels, Vjaceslavs Sitikovs
Jazyk:	angličtina
Rok vydání:	2007
Předmět:	Regression approximation model selection heuristic search model evaluation Mathematics QA1-939
Zdroj:	Mathematical Modelling and Analysis, Vol 12, Iss 1 (2007)
Druh dokumentu:	article
ISSN:	1392-6292 1648-3510
DOI:	10.3846/1392-6292.2007.12.81-90
Popis:	The main problem in regression model selection is finding the best model that best fits the data, i.e. it does not neither overfit nor underfit. The aim of this work is to show one of possible ways to find adequate nonlinear regression models (parametric) of technical systems based on an heuristic search and analytical optimality evaluation approach by taking into consideration the computational power of modern computers. First Published Online: 14 Oct 2010
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/a81d570c31e94db490a5e8174dd22e27 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF