Diagnostics of data outliers using subspace identification

Autor:	Jaafar AlMutawa
Rok vydání:	2013
Předmět:	Identification (information) Subspace system identification State-space representation Outlier General Medicine Data mining computer.software_genre computer Subspace topology Mathematics
Zdroj:	MIM
ISSN:	1474-6670
DOI:	10.3182/20130619-3-ru-3018.00598
Popis:	We propose a diagnostics technique for the state space model fitting formed by deleting observations from the data and measuring the change in the estimates of the parameters. A method is proposed for distinguishing an observational outlier from an innovational one. The presented subspace system identification algorithm is robust and less sensitive to outliers. We give a numerical result to show effectiveness of the proposed method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::243754d73ca6e2a9ac152157c3d16cc3 https://doi.org/10.3182/20130619-3-ru-3018.00598 Zobrazit plný text záznamu