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Iterative estimators of parameters in linear models with partially variant coefficients
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0002-9706-5008
2007 (English)In: International Journal of Applied Mathematics and Computer Sciences, ISSN 1307-6906, Vol. 17, no 2, 179-187 p.Article in journal (Refereed) Published
Abstract [en]

A new kind of linear model with partially variant coefficients is proposed and a series of iterative algorithms are introduced and verified. The new generalized linear model includes the ordinary linear regression model as a special case. The iterative algorithms efficiently overcome some difficulties in computation with multidimensional inputs and incessantly appending parameters. An important application is described at the end of this article, which shows that this new model is reasonable and applicable in practical fields.

Place, publisher, year, edition, pages
2007. Vol. 17, no 2, 179-187 p.
Keyword [en]
linear model, parameter estimation, iterative algorithms, variant coefficients
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-62897DOI: 10.2478/v10006-007-0017-0Scopus ID: 2-s2.0-34547547324OAI: oai:DiVA.org:kth-62897DiVA: diva2:481305
Note

QC 20120123

Available from: 2012-01-20 Created: 2012-01-20 Last updated: 2017-12-08Bibliographically approved

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Meinke, Karl

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