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The abscissa of convergence of the Laplace transform

Part of: Distribution theory - Probability Harmonic analysis in one variable Stochastic processes

Published online by Cambridge University Press:  14 July 2016

Peter Hall ,
Jozef L. Teugels  and
Ann Vanmarcke
Peter Hall*
Affiliation:
Australian National University
Jozef L. Teugels*
Affiliation:
Katholieke Universiteit Leuven
Ann Vanmarcke*
Affiliation:
Katholieke Universiteit Leuven
*
∗Postal address, Department of Statistics, Faculty of Economics and Commerce, Australian National University, GPO Box 4, Canberra ACT 2601, Australia.
∗∗Postal address: Katholieke Universiteit Leuven, Departement Wiskunde, Celestijnenlaan 200 B, 3001 Leuven (Heverlee), Belgium.
∗∗Postal address: Katholieke Universiteit Leuven, Departement Wiskunde, Celestijnenlaan 200 B, 3001 Leuven (Heverlee), Belgium.
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Abstract

Assume that we want to estimate – σ, the abscissa of convergence of the Laplace transform. We show that no non-parametric estimator of σ can converge at a faster rate than (log n)–1, where n is the sample size. An optimal convergence rate is achieved by an estimator of the form where xn = O(log n) and is the mean of the sample values overshooting xn. Under further parametric restrictions this (log n)–1 phenomenon is also illustrated by a weak convergence result.

Keywords

CONVERGENCE RATEDIVERGENCE POINTEMPIRICAL METHODEXTREME VALUE THEORYMINIMAX

MSC classification

Primary: 60E10: Characteristic functions; other transforms
Secondary: 42A61: Probabilistic methods 60G70: Extreme value theory; extremal processes
Type
Research Papers
Information
Journal of Applied Probability , Volume 29 , Issue 2 , June 1992 , pp. 353 - 362
Copyright
Copyright © Applied Probability Trust 1992 

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References

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