SiZer for exploration of structures in curves

被引：432

作者：

Chaudhuri, P ^{[1
]}

Marron, JS

机构：

[1] Indian Stat Inst, Theoret Stat & Math Unit, Kolkata 700035, W Bengal, India

[2] Univ N Carolina, Dept Stat, Chapel Hill, NC 27599 USA

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 1999年 / 94卷 / 447期

关键词：

confidence bands; curve estimation; kernel estimates; local polynomials; nonparametric smoothing; scale space; significant features; SiZer map;

D O I：

10.2307/2669996

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];

摘要：

In the use of smoothing methods in data analysis, an important question is which observed features are "really there," as opposed to being spurious sampling artifacts. An approach is described based on scale-space ideas originally developed in the computer vision literature. Assessment of SIgnificant ZERo crossings of derivatives results in the SiZer map, a graphical device for display of significance of features with respect to both location and scale. Here "scale" means "level of resolution"; that is, "bandwidth."

引用

页码：807 / 823

页数：17

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