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r=kdtree_ksrmv(x,y,hx,z) KDTREE_KSRMV Multivariate kernel smoothing regression with kd-tree acceleration
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Efficient Kernel Smoothing Regression using KD-Tree

24 Mar 2008 (Updated 25 Mar 2008)

Efficiency improved multivariant kernel regression using kd-tree

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Description	Kernel regression is a power full tool for smoothing, image and signal processing, etc. However, it is computationally expensive when it is extented for multivariant cases. The efficiency can be improved by only using neighbors within the effective range arond a regression point. To improve the efficiency further, the kd-tree tool developed by Steven Michael http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=7030&objectType=file is used to efficiently identify points within a range. For large data sets, this code can reduce computation time by 3 to 5 times.
Acknowledgements	Kd Tree Nearest Neighbor And Range Search and Multivariant Kernel Regression And Smoothing inspired this file.
MATLAB release	MATLAB 7.5 (R2007b)

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Everyone's Tags	kernel density estimation(2), kernel regression, kernel smoothing, nonpa(2), probability, statistics
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15 Jul 2010	Turkay YILDIZ
05 Apr 2009	V. Poor