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A simulation study of some biasing parameters for the ridge type estimation of Poisson regression
Department of Mathematics and Statistics, Florida International University, Miami, Florida, USA.
Jönköping University, Jönköping International Business School, JIBS, Statistics.
Jönköping University, Jönköping International Business School, JIBS, Statistics.
2015 (English)In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 44, no 4, p. 943-957Article in journal (Refereed) Published
Abstract [en]

This paper proposes several estimators for estimating the ridge parameter k based for Poisson ridge regression (RR) model. These estimators have been evaluated by means of Monte Carlo simulations. As performance criteria, we have calculated the mean squared error (MSE), the mean value and the standard deviation of k. The first criterion is commonly used, while the other two have never been used when analyzing Poisson RR. However, these performance criterion are very informative because, if several estimators have an equal estimated MSE then those with low average value and standard deviation of k should be preferred. Based on the simulated results we may recommend some biasing parameters which may be useful for the practitioners in the field of health, social and physical sciences.

Place, publisher, year, edition, pages
2015. Vol. 44, no 4, p. 943-957
Keywords [en]
Estimation, MSE, Multicollinearity, Poisson, Ridge regression, Simulation, Primary 62J07, Secondary 62F10
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:hj:diva-20959DOI: 10.1080/03610918.2013.796981ISI: 000342295500009Scopus ID: 2-s2.0-84908519267Local ID: IHHEFSISOAI: oai:DiVA.org:hj-20959DiVA, id: diva2:616825
Available from: 2013-04-18 Created: 2013-04-18 Last updated: 2017-12-06Bibliographically approved

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Shukur, GhaziMånsson, Kristofer

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  • apa
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
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