Robust online scale estimation in time series: A model-free approach

被引:12
|
作者
Gelper, Sarah [1 ]
Schettlinger, Karen [2 ]
Croux, Christophe [1 ]
Gather, Ursula [2 ]
机构
[1] Katholieke Univ Leuven, Fac Business & Econ, B-3000 Louvain, Belgium
[2] Tech Univ Dortmund, Fak Stat, D-44221 Dortmund, Germany
关键词
Breakdown point; Influence function; Online monitoring; Outliers; Robust scale estimation; SIGNAL EXTRACTION; REGRESSION; CURVE;
D O I
10.1016/j.jspi.2008.04.018
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
This paper presents variance extraction procedures for univariate time series. The volatility of a times series is monitored allowing for non-linearities, jumps and outliers in the level. The volatility is measured using the height of triangles formed by consecutive observations of the time series. This idea was proposed by Rousseeuw and Hubert [1996. Regression-free and robust estimation of scale for bivariate data. Comput. Statist. Data Anal. 21, 67-85] in the bivariate setting. This paper extends their procedure to apply for online scale estimation in time series analysis. The statistical properties of the new methods are derived and finite sample properties are given. A financial and a medical application illustrate the use of the procedures. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:335 / 349
页数:15
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