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Tree-Structured Histogram Estimation Based on a Simple Class of Wavelets

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Author Info
Joachim Engel
Abstract

Adaptive multivariate histograms that are obtained through recursive partitioning of the sample space are studied. The central idea is to consider the tree-structured histogram as a wavelet estimator based on the orthogonal system of Haar functions. From the formula for the mean squared error a spatially adaptive data-driven smoothing method is proposed leading to an unequal bin width histogram.

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Publisher Info
Paper provided by University of Bonn, Germany in its series Discussion Paper Serie A with number 415.

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Length: 14 pages
Date of creation: Aug 1993
Date of revision:
Handle: RePEc:bon:bonsfa:415

Contact details of provider:
Postal: Bonn Graduate School of Economics, University of Bonn, Adenauerallee 24 - 26, 53113 Bonn, Germany
Fax: +49 228 73 9221
Web page: http://www.bgse.uni-bonn.de/index.php?id=517

For technical questions regarding this item, or to correct its listing, contact: (Daniel Park).

Related research
Keywords: Multivariate histogram adaptive histogram tree-structured methods wavelets Haar functions

Statistics
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