Confidence Interval for Shrinkage Parameters in Ridge Regression

In ridge regression, the estimation of ridge parameter k is an important problem. There are several methods available in the literature to do this job some what efficiently. However, no attempts were made to suggest a confidence interval for the ridge parameter using the knwoledge from the data. In...

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Bibliographic Details
Published in:Communications in statistics. Theory and methods 2009-01, Vol.38 (19), p.3489-3497
Main Authors: Alheety, M. I., Ramanathan, T. V.
Format: Article
Language:English
Subjects:
Exact sciences and technology
General topics
Linear inference, regression
Mathematics
Nonparametric inference
Parametric inference
Probability and statistics
Ridge regression
Sciences and techniques of general use
Shrinkage parameter
Simulation study
Statistics
Venables method
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Summary:In ridge regression, the estimation of ridge parameter k is an important problem. There are several methods available in the literature to do this job some what efficiently. However, no attempts were made to suggest a confidence interval for the ridge parameter using the knwoledge from the data. In this article, we propose a data dependent confidence interval for the ridge parameter k. The method of obtaining the confidence interval is illustrated with the help of a data set. A simulation study indicates that the empirical coverage probability of the suggested confidence intervals are quite high.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610920802585856