非参数密度估计的样条局部基方法

IF 11 Q1 STATISTICS & PROBABILITY Statistics Surveys Pub Date : 2023-01-01 DOI:10.1214/23-ss142
J. Lars Kirkby, Álvaro Leitao, Duy Nguyen
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引用次数: 1

摘要

本文综述了非参数密度估计的样条局部基方法。特别注意的是最近在理论和方法上都取得进展的b样条密度估计。这些估计器在统计学中占据了一个非常有趣的空间,它恰好位于许多统计框架的横截面上。提出了新的见解、实验和分析,将各种估计概念置于统一的上下文中,同时将其与更熟悉的核密度估计上下文中进行类比和对比。与核密度估计不同,局部基估计的研究尚未完全成熟,本工作也旨在突出现有文献中值得进一步研究的空白。
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Spline local basis methods for nonparametric density estimation
This work reviews the literature on spline local basis methods for non-parametric density estimation. Particular attention is paid to B-spline density estimators which have experienced recent advances in both theory and methodology. These estimators occupy a very interesting space in statistics, which lies aptly at the cross-section of numerous statistical frameworks. New insights, experiments, and analyses are presented to cast the various estimation concepts in a unified context, while parallels and contrasts are drawn to the more familiar contexts of kernel density estimation. Unlike kernel density estimation, the study of local basis estimation is not yet fully mature, and this work also aims to highlight the gaps in existing literature which merit further investigation.
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来源期刊
Statistics Surveys
Statistics Surveys STATISTICS & PROBABILITY-
CiteScore
11.70
自引率
0.00%
发文量
5
期刊介绍: Statistics Surveys publishes survey articles in theoretical, computational, and applied statistics. The style of articles may range from reviews of recent research to graduate textbook exposition. Articles may be broad or narrow in scope. The essential requirements are a well specified topic and target audience, together with clear exposition. Statistics Surveys is sponsored by the American Statistical Association, the Bernoulli Society, the Institute of Mathematical Statistics, and by the Statistical Society of Canada.
期刊最新文献
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