Premium
A FINE‐TUNED ESTIMATOR OF A GENERAL CONVERGENCE RATE
Author(s) -
Mcelroy Tucker,
Politis Dimitris N.
Publication year - 2008
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/j.1467-842x.2007.00496.x
Subject(s) - estimator , mathematics , convergence (economics) , rate of convergence , statistics , econometrics , mathematical optimization , computer science , economics , computer network , channel (broadcasting) , economic growth
Summary 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.