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A Note on a commonly used ridge regression Monte Carlo design
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics.
2014 (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 p distinct regressor eigenvalues should not be evaluated through Monte Carlo designs using only two distinct eigenvalues.

Place, publisher, year, edition, pages
London: Taylor & Francis Group, 2014. Vol. 44, no 10, p. 2176-2179
Keywords [en]
Design matrix, Excess mean square error, Monte carlo simulation, Multicollinearity, Ridge regression
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Other Social Sciences
Identifiers
URN: urn:nbn:se:hj:diva-20545DOI: 10.1080/03610926.2013.775299ISI: 000356857700013Scopus ID: 2-s2.0-84930698293OAI: oai:DiVA.org:hj-20545DiVA, id: diva2:605449
Available from: 2013-02-14 Created: 2013-02-14 Last updated: 2017-12-06Bibliographically approved

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Holgersson, Thomas

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