This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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309
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Computing
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Abstract - #308036 |
Title:
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Knot Selection for Least Squares and Penalized Splines
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Author(s):
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Steven Spiriti*+ and Randall Eubank and Philip Smith and Dennis Young
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Companies:
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Arizona State University and Arizona State University and Texas Tech University and Arizona State University
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Address:
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1812 E. San Miguel, Phoenix, AZ, 85016,
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Keywords:
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blind random search ;
genetic algorithm ;
golden section ;
parallel computing ;
free-knot splines ;
penalized splines
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Abstract:
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We compare techniques for computing free-knot splines and penalized splines, or P-splines. Although P-splines are conventionally fitted using fixed knot locations, we examine the case where P-splines are fitted using optimal knot locations. Standard optimization algorithms do not perform adequately when optimizing the knot locations; consequently, two random search alternatives are proposed: blind search with golden section and a genetic algorithm. A simulation study is performed, comparing the free-knot algorithms to fixed-knot algorithms and to smoothing splines. It is found that the free-knot algorithms outperform their fixed-knot alternatives.
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