Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-23T13:42:38.615Z Has data issue: false hasContentIssue false

On the weak limit law of the maximal uniform k-spacing

Published online by Cambridge University Press:  25 July 2016

Aleksandar Mijatović*
Affiliation:
King's College London
Vladislav Vysotsky*
Affiliation:
Arizona State University, Imperial College London, and St. Petersburg Department of Steklov Mathematical Institute
*
Department of Mathematics, King's College London, Strand, London WC2R 2LS, UK. Email address: [email protected]
School of Mathematical and Statistical Sciences, Arizona State University, PO Box 871804, Tempe, AZ 85287, USA. Email address: [email protected]

Abstract

In this paper we give a simple proof of a limit theorem for the length of the largest interval straddling a fixed number of points that are independent and uniformly distributed on a unit interval. The key step in our argument is a classical theorem of Watson on the maxima of m-dependent stationary stochastic sequences.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Deheuvels, P. (1982).Strong limiting bounds for maximal uniform spacings.Ann. Prob. 10,10581065.CrossRefGoogle Scholar
[2] Deheuvels, P. and Devroye, L. (1984).Strong laws for the maximal k-spacing when kclogn .Z. Wahrscheinlichkeitsth. 66,315334.CrossRefGoogle Scholar
[3] Devroye, L. (1981).Laws of the iterated logarithm for order statistics of uniform spacings.Ann. Prob. 9,860867.CrossRefGoogle Scholar
[4] Pyke, R. (1965).Spacings.J. R. Statist. Soc. B. 27,395449.Google Scholar
[5] Shorack, G. R. and Wellner, J. A. (1986).Empirical Processes with Applications to Statistics.John Wiley,New York.Google Scholar
[6] Watson, G. S. (1954).Extreme values in samples from m-dependent stationary stochastic processes.Ann. Math. Statist. 25,798800.CrossRefGoogle Scholar