迭代数据锐化

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-05-31 DOI:10.1080/10618600.2024.2362219

Hanxiao Chen, W. John Braun, Xiaoping Shi

引用次数: 0

摘要

核回归中的数据锐化已被证明是减少偏差的有效方法，同时对方差的影响最小。早先对数据锐化程序进行迭代的努力...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Iterated Data Sharpening

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.