NDLI: On the computer intensive methods in model selection

Content Provider	IEEE Xplore Digital Library
Author	Iskander, D.R. Alkhaldi, W. Zoubir, A.M.
Copyright Year	2008
Description	Author affiliation: Sch. of Optometry, Queensland Univ. of Technol., Brisbane, QLD (Iskander, D.R.)
Abstract	Bootstrap-based model selection has been shown in many practical instances to be superior to classical methods such the AIC and MDL. This is particularly noticeable when the distribution of modelling noise is unknown and/or when the available data samples are small. One of the main problems of using bootstrap model selection with real data is the necessity of tuning the residual scaling parameter or estimating the length of a sub-sample. Recently, we have developed a new hook and loop (HL) resampling plane, in which the scaling of the residuals is avoided. Here, we compare the performance of the range of resampling planes that can be used in the context of model selection and show that the HL-based model selection is superior to its predecessors. Moreover, in the context of fitting parametric models to corneal data measured by videokeratoscopes, the HL provides results that are consistent with clinical expectations.
Starting Page	3461
Ending Page	3464
File Size	190830
Page Count	4
File Format	PDF
ISBN	9781424414833
ISSN	15206149
DOI	10.1109/ICASSP.2008.4518396
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context modeling Optical signal processing Optical computing Lenses Nonlinear optics Kelvin Australia Parameter estimation Parametric statistics Surface fitting corneal surface modelling model/order selection resampling planes
Content Type	Text
Resource Type	Article

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