AN EFFICIENT ALGORITHM FOR THE LEAST-SQUARES CROSS-VALIDATION WITH SYMMETRICAL AND POLYNOMIAL KERNELS

被引：0

作者：

LEE, BG ^{[1
]}

KIM, BC ^{[1
]}

机构：

[1] KOREA ADV INST SCI & TECHNOL,SEOUL 131,SOUTH KOREA

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 1990年 / 19卷 / 04期

关键词：

PROBABILITY DENSITY ESTIMATION; LEAST-SQUARES CROSS-VALIDATION; CONVOLUTION; SYMMETRICAL AND POLYNOMIAL KERNELS;

D O I：

10.1080/03610919008812933

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：

The least-squares cross-validation is a completely automatic method for choosing the smoothing parameter in probability density estimation but this method consume large amounts of computer time. This article concerns an efficient computational algorithm for this method when the kernel is symmetric and polynomial functions.

引用

页码：1513 / 1522

页数：10

共 3 条

[1] A least-squares cross-validation bandwidth selection approach in pair correlation function estimations
Guan, Yongtao
STATISTICS & PROBABILITY LETTERS, 2007, 77 (18) : 1722 - 1729
[2] Comparison of least-squares cross-validation bandwidth options for kernel home-range estimation
Gitzen, RA
Millspaugh, JJ
WILDLIFE SOCIETY BULLETIN, 2003, 31 (03): : 823 - 831
[3] Likelihood cross-validation versus least squares cross-validation for choosing the smoothing parameter in kernel home-range analysis
Horne, Jon S.
Garton, Edward O.
JOURNAL OF WILDLIFE MANAGEMENT, 2006, 70 (03) : 641 - 648

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