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A note on a commonly used ridge regression Monte Carlo design
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University.
2015 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 44, no 10, p. 2176-2179Article in journal (Refereed) Published
Abstract [en]

Ridge estimators are usually examined through Monte Carlo simulations since their properties are difficult to obtain analytically. In this paper we argue that a simulation design commonly used in the literature will give biased results of Monte Carlo simulations in favour of ridge regression over ordinary least square (OLS) estimators. Specifically, it is argued that the properties of ridge estimators that are functions of pdistinct regressor eigenvalues should not be evaluated through Monte Carlo designs using only two distinct eigenvalues.

Place, publisher, year, edition, pages
2015. Vol. 44, no 10, p. 2176-2179
Keywords [en]
Design matrix, Excess mean square error, Monte Carlo simulation, Multicollinearity, Ridge regression
National Category
Probability Theory and Statistics
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-28540DOI: 10.1080/03610926.2013.775299ISI: 000356857700013Scopus ID: 2-s2.0-84930698293OAI: oai:DiVA.org:lnu-28540DiVA, id: diva2:643744
Available from: 2013-08-28 Created: 2013-08-27 Last updated: 2017-12-06Bibliographically approved

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Holgersson, Thomas

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