首页> 外文OA文献 >Robust online scale estimation in time series: a model-free approach
【2h】

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

机译:时间序列中可靠的在线规模估算:无模型方法

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 oftriangles 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, Computational Statistics and Data Analysis, 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 newmethods are derived and finite sample properties are given. A financial and a medical application illustrate the use of the procedures.
机译:本文介绍了单变量时间序列的方差提取过程。监视时间序列的波动性,以考虑水平中的非线性,跳跃和离群值。使用时间序列的连续观察所形成的三角形的高度来测量波动率。这个想法由Rousseeuw和Hubert提出(1996年,在双变量环境下,无回归且鲁棒的双变量数据规模估计,计算统计和数据分析,21,67 {85)。本文扩展了其程序,以在时间序列分析中应用在线规模估计。推导了新方法的统计性质,并给出了有限样本性质。财务和医疗应用程序说明了该程序的使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号