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Title: Ridge Estimator Revisited (English)
Author: Kubáček, Lubomír
Language: English
Journal: Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
ISSN: 0231-9721
Volume: 51
Issue: 2
Year: 2012
Pages: 73-86
Summary lang: English
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Category: math
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Summary: Bad conditioned matrix of normal equations in connection with small values of model parameters is a source of problems in parameter estimation. One solution gives the ridge estimator. Some modification of it is the aim of the paper. The behaviour of it in models with constraints is investigated as well. (English)
Keyword: linear model
Keyword: ridge estimator
Keyword: constraints
MSC: 62J05
MSC: 62J07
idZBL: Zbl 06204932
idMR: MR3058875
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Date available: 2012-11-26T10:19:20Z
Last updated: 2014-03-12
Stable URL: http://hdl.handle.net/10338.dmlcz/143069
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Reference: [1] Fišerová, E., Kubáček, L., Kunderová, P.: Linear Statistical Models: Regularity and Singularities. Academia, Praha, 2007.
Reference: [2] Harville, D. A.: Matrix Algebra for a Statistician’s Perspective. Springer, New York– Berlin–Heidelberg–Barcelona–Hong Kong–London–Milan–Paris–Singapore–Tokyo, 1997. MR 1467237
Reference: [3] Hoerl, A. E., Kennard, R. W.: Ridge regression: Biased eastimation for nonorthogonal problems. Technometrics 12 (1970), 55–67. 10.1080/00401706.1970.10488634
Reference: [4] Hoerl, A. E., Kennard, R. W.: Ridge regression: Application to nonorthogonal problems. Technometrics 12 (1970), 69–82. 10.1080/00401706.1970.10488635
Reference: [5] Goldstein, M., Smith, A. F. M.: Ridge–type estimators for regression analysis. Journal of the Royal Statistical Society, Series B 36 (1974), 284–291 Zbl 0287.62036, MR 0418342
Reference: [6] Rao, C. R., Mitra, S. K.: Generalized Inverse of Matrices and its Applications. Wiley, New York–London–Sydney–Toronto, 1971. Zbl 0236.15005, MR 0338013
Reference: [7] Theobald, C. M.: Generalizations of mean square error applied to ridge regression. Journal of the Royal Statistical Society, Series B 36 (1974), 103–106. Zbl 0282.62055, MR 0368328
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