Difference: Papers20100623102319 (1 vs. 4)

Revision 42010-08-13 - TheresiaFreska

 
META TOPICPARENT name="AI_GEOSTATSPapers"
Title: Nonparametric Spatial Rainfall Characterization Using Adaptive Kernel Estimator

Date: 1 May 1998

Authors: Alaa Ali

Link: Ali.pdf

Abstract:

A nonparametric statistical tool based on kernel function estimation is developed for spatial rainfall characterization. In this method, observations closer to the point of estimate are weighted higher using kernel function with a prescribed bandwidth. The kernel bandwidth is local and it extends only to the Kth Nearest Neighbor, KNN, observation. An optimal value for KNN is selected by cross validation. Unlike Kriging, the underlying stochastic process is not assumed to be stationary. An application of this model using rainfall data is presented.

Reference:

Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, pp. 34-43, 1998.

KEYWORDS: nonparametric statistics, Kth nearest neighbor, kernel estimator, nonstationarity, cross validation

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Revision 32010-07-24 - TWikiAdminUser

 
META TOPICPARENT name="AI_GEOSTATSPapers"
Title: Nonparametric Spatial Rainfall Characterization Using Adaptive Kernel Estimator
Changed:
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>		Date: 1 May 1998
  Authors: Alaa Ali
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<		Link: fileadmin/Documents/SIC97_GIDA/Ali.pdf
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>		Link: Ali.pdf
  Abstract:
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>		A nonparametric statistical tool based on kernel function estimation is developed for spatial rainfall characterization. In this method, observations closer to the point of estimate are weighted higher using kernel function with a prescribed bandwidth. The kernel bandwidth is local and it extends only to the Kth Nearest Neighbor, KNN, observation. An optimal value for KNN is selected by cross validation. Unlike Kriging, the underlying stochastic process is not assumed to be stationary. An application of this model using rainfall data is presented.
 Reference:

Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, pp. 34-43, 1998.

Deleted:
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<		Abstract

A nonparametric statistical tool based on kernel function estimation is developed for spatial rainfall characterization. In this method, observations closer to the point of estimate are weighted higher using kernel function with a prescribed bandwidth. The kernel bandwidth is local and it extends only to the Kth Nearest Neighbor, KNN, observation. An optimal value for KNN is selected by cross validation. Unlike Kriging, the underlying stochastic process is not assumed to be stationary. An application of this model using rainfall data is presented.

 KEYWORDS: nonparametric statistics, Kth nearest neighbor, kernel estimator, nonstationarity, cross validation

-- TWikiAdminUser - 2010-06-16

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META FILEATTACHMENT attachment="Ali.pdf" attr="" comment="" date="1280006804" name="Ali.pdf" path="Ali.pdf" size="739284" stream="Ali.pdf" tmpFilename="\rJIV9r3GL1" user="BaseUserMapping_333" version="2"

Revision 22010-07-23 - TWikiAdminUser

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META TOPICPARENT name="GeostatisticsPapers"
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META TOPICPARENT name="AI_GEOSTATSPapers"
 Title: Nonparametric Spatial Rainfall Characterization Using Adaptive Kernel Estimator

Date:

Authors: Alaa Ali

Link: fileadmin/Documents/SIC97_GIDA/Ali.pdf

Abstract:

Reference:

Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, pp. 34-43, 1998.

Abstract

A nonparametric statistical tool based on kernel function estimation is developed for spatial rainfall characterization. In this method, observations closer to the point of estimate are weighted higher using kernel function with a prescribed bandwidth. The kernel bandwidth is local and it extends only to the Kth Nearest Neighbor, KNN, observation. An optimal value for KNN is selected by cross validation. Unlike Kriging, the underlying stochastic process is not assumed to be stationary. An application of this model using rainfall data is presented.

KEYWORDS: nonparametric statistics, Kth nearest neighbor, kernel estimator, nonstationarity, cross validation

-- TWikiAdminUser - 2010-06-16

Revision 12010-06-23 - TWikiAdminUser

 
META TOPICPARENT name="GeostatisticsPapers"
Title: Nonparametric Spatial Rainfall Characterization Using Adaptive Kernel Estimator

Date:

Authors: Alaa Ali

Link: fileadmin/Documents/SIC97_GIDA/Ali.pdf

Abstract:

Reference:

Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, pp. 34-43, 1998.

Abstract

A nonparametric statistical tool based on kernel function estimation is developed for spatial rainfall characterization. In this method, observations closer to the point of estimate are weighted higher using kernel function with a prescribed bandwidth. The kernel bandwidth is local and it extends only to the Kth Nearest Neighbor, KNN, observation. An optimal value for KNN is selected by cross validation. Unlike Kriging, the underlying stochastic process is not assumed to be stationary. An application of this model using rainfall data is presented.

KEYWORDS: nonparametric statistics, Kth nearest neighbor, kernel estimator, nonstationarity, cross validation

-- TWikiAdminUser - 2010-06-16

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