Clements, A.E., Hurn, A.S. and Lindsay, K.A. (2003) Mobius-like mappings and their use in kernel density estimation. Journal of the American Statistical Association, 98(464), pp. 993-1000. (doi: 10.1198/016214503000000945)
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Publisher's URL: http://dx.doi.org/10.1198/016214503000000945
Abstract
It is well known that the manipulation of sample data by means of a parametric function can improve the performance of kernel density estimation. This article proposes a two-parameter Mobius-like function to map sample data drawn from a semi-infinite space into [−1,1). A standard kernel method is then used to estimate the density. The proposed method is shown to yield effective estimates of density and is computationally more efficient than other well-known transformation methods. The efficacy of the technique is demonstrated in a practical setting by application to two datasets.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Lindsay, Professor Kenneth |
Authors: | Clements, A.E., Hurn, A.S., and Lindsay, K.A. |
Subjects: | Q Science > QA Mathematics |
College/School: | College of Science and Engineering > School of Mathematics and Statistics > Mathematics |
Journal Name: | Journal of the American Statistical Association |
ISSN: | 0162-1459 |
ISSN (Online): | 1537-274X |
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