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Title: On the Equivalence between Orthogonal Regression and Linear Model with Type-II Constraints (English)
Author: Donevska, Sandra
Author: Fišerová, Eva
Author: Hron, Karel
Language: English
Journal: Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
ISSN: 0231-9721
Volume: 50
Issue: 2
Year: 2011
Pages: 19-27
Summary lang: English
Category: math
Summary: Orthogonal regression, also known as the total least squares method, regression with errors-in variables or as a calibration problem, analyzes linear relationship between variables. Comparing to the standard regression, both dependent and explanatory variables account for measurement errors. Through this paper we shortly discuss the orthogonal least squares, the least squares and the maximum likelihood methods for estimation of the orthogonal regression line. We also show that all mentioned approaches lead to the same estimates in a special case. (English)
Keyword: linear regression model with type-II constraints
Keyword: orthogonal regression
Keyword: estimation
MSC: 62F10
MSC: 62J05
idZBL: Zbl 1244.62097
idMR: MR2920705
Date available: 2011-12-16T14:43:51Z
Last updated: 2013-09-18
Stable URL:
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