Identification of Outliers

鉴定(生物学) 离群值 计算机科学 统计 数学 生物 植物
作者
D. M. Hawkins
出处
期刊:Springer eBooks [Springer Nature]
被引量:2656
标识
DOI:10.1007/978-94-015-3994-4
摘要

The problem of outliers is one of the oldest in statistics, and during the last century and a half interest in it has waxed and waned several times. Currently it is once again an active research area after some years of relative neglect, and recent work has solved a number of old problems in outlier theory, and identified new ones. The major results are, however, scattered amongst many journal articles, and for some time there has been a clear need to bring them together in one place. That was the original intention of this monograph: but during execution it became clear that the existing theory of outliers was deficient in several areas, and so the monograph also contains a number of new results and conjectures. In view of the enormous volume ofliterature on the outlier problem and its cousins, no attempt has been made to make the coverage exhaustive. The material is concerned almost entirely with the use of outlier tests that are known (or may reasonably be expected) to be optimal in some way. Such topics as robust estimation are largely ignored, being covered more adequately in other sources. The numerous ad hoc statistics proposed in the early work on the grounds of intuitive appeal or computational simplicity also are not discussed in any detail.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
dc123456发布了新的文献求助10
1秒前
1秒前
无心的怜烟应助eternity136采纳,获得10
2秒前
共享精神应助魁梧的鲂采纳,获得10
3秒前
坦率续发布了新的文献求助10
3秒前
4秒前
朴素尔蓝完成签到,获得积分10
5秒前
zjspidany应助敏敏采纳,获得10
5秒前
香蕉觅云应助Jimmy采纳,获得30
7秒前
iNk应助显隐采纳,获得10
8秒前
8秒前
lmy发布了新的文献求助10
8秒前
dc123456完成签到,获得积分10
9秒前
爱静静应助rysben采纳,获得10
9秒前
9秒前
悠然xz发布了新的文献求助10
9秒前
能干的茗发布了新的文献求助10
9秒前
10秒前
11秒前
爱静静应助fatcat采纳,获得10
12秒前
洁白的宇天完成签到 ,获得积分10
13秒前
13秒前
英俊的铭应助甘蔗侠采纳,获得10
14秒前
小王发布了新的文献求助10
14秒前
小刘小刘发布了新的文献求助10
14秒前
黎明完成签到,获得积分10
16秒前
香蕉觅云应助鸿鹄在天涯采纳,获得10
17秒前
Ava应助坦率续采纳,获得10
18秒前
木子青山完成签到,获得积分10
18秒前
20秒前
英姑应助能干的茗采纳,获得10
20秒前
20秒前
丘比特应助小王采纳,获得10
21秒前
22秒前
chenchenchen发布了新的文献求助10
23秒前
24秒前
彭于晏应助NINI采纳,获得10
24秒前
25秒前
柚子发布了新的文献求助10
25秒前
26秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Cognitive Paradigms in Knowledge Organisation 2000
Introduction to Spectroscopic Ellipsometry of Thin Film Materials Instrumentation, Data Analysis, and Applications 1800
Natural History of Mantodea 螳螂的自然史 1000
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
How Maoism Was Made: Reconstructing China, 1949-1965 800
Barge Mooring (Oilfield Seamanship Series Volume 6) 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3314052
求助须知:如何正确求助?哪些是违规求助? 2946471
关于积分的说明 8530176
捐赠科研通 2622111
什么是DOI,文献DOI怎么找? 1434341
科研通“疑难数据库(出版商)”最低求助积分说明 665205
邀请新用户注册赠送积分活动 650804