Bandwidth;
Data smoothing;
Kernel regression;
Locational entropy;
Subjective probabilities;
D O I:
10.1016/j.spl.2012.12.006
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
Data smoothing or regression kernels based on locational entropy embody the principle that observations towards the extremes of the chosen data window should provide less information than those at the midpoint. Weight patterns can be flexible, depending on the choice of prior information density. (C) 2012 Elsevier B.V. All rights reserved.
机构:
College of Engineering and Computer Science, Australian National University, Canberra, ACT 0200, AustraliaCollege of Engineering and Computer Science, Australian National University, Canberra, ACT 0200, Australia
Shi, Qinfeng
Petterson, James
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h-index: 0
机构:
Statistical Machine Learning, National ICT Australia, Locked Bag 8001, Canberra, ACT 2601, AustraliaCollege of Engineering and Computer Science, Australian National University, Canberra, ACT 0200, Australia
Petterson, James
Dror, Gideon
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h-index: 0
机构:
Division of Computer Science, Academic College of Tel-Aviv-Yaffo, IsraelCollege of Engineering and Computer Science, Australian National University, Canberra, ACT 0200, Australia
Dror, Gideon
Langford, John
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h-index: 0
机构:
Yahoo Research, New York, NY, United States
Yahoo Research, New York, NY, United StatesCollege of Engineering and Computer Science, Australian National University, Canberra, ACT 0200, Australia
Langford, John
Smola, Alex
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h-index: 0
机构:
Yahoo Research, New York, NY, United States
Yahoo Research, New York, NY, United StatesCollege of Engineering and Computer Science, Australian National University, Canberra, ACT 0200, Australia
Smola, Alex
Vishwanathan, S.V.N.
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h-index: 0
机构:
Department of Statistics, Purdue University, IN, AustraliaCollege of Engineering and Computer Science, Australian National University, Canberra, ACT 0200, Australia