首页 | 本学科首页   官方微博 | 高级检索  
     


A FINE-TUNED ESTIMATOR OF A GENERAL CONVERGENCE RATE
Authors:Tucker  Mcelroy   Dimitris N.  Politis
Affiliation:US Census Bureau and University of California at San Diego
Abstract:A general rate estimation method based on the in‐sample evolution of appropriately chosen diverging/converging statistics has recently been proposed by D.N. Politis [C. R. Acad. Sci. Paris, Ser. I, vol. 335, pp. 279–282, 2002] and T. McElroy & D.N. Politis [Ann. Statist., vol. 35, pp. 1827–1848, 2007]. In this paper, we show how a modification of the original estimators achieves a competitive rate of convergence. The modified estimators require the choice of a tuning parameter; an optimal such choice is generally a non‐trivial problem in practice. Some discussion to that effect is given, as well as a small simulation study in a heavy‐tailed setting.
Keywords:heavy-tail index    rate of convergence    stationary sequence    time series
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号