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Limit laws on extremes of nonhomogeneous Gaussian random fields

Published online by Cambridge University Press:  15 September 2017

Zhongquan Tan*
Affiliation:
Zhejiang University and Jiaxing University
*
* Postal address: College of Mathematics, Physics and Information Engineering, Jiaxing University, Lianglin Campus, Jiaxing, 314001, P.R. China. Email address: [email protected]

Abstract

In this paper, by using the tail asymptotics derived by Dębicki et al. (2016), we prove the Gumbel limit laws for the maximum of a class of nonhomogeneous Gaussian random fields. As an application of the main results, we derive the Gumbel limit law for Shepp statistics of fractional Brownian motion and Gaussian integrated processes.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 2017 

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References

Albin, J. M. P. (1990). On extremal theory for stationary processes. Ann. Prob. 18, 92128. CrossRefGoogle Scholar
Berman, S. M. (1974). Sojourns and extremes of Gaussian processes. Ann. Prob. 2, 9991026. Google Scholar
Bickel, P. J. and Rosenblatt, M. (1973). On some global measures of the deviations of density function estimates. Ann. Statist. 1, 10711095. (Correction: 3 (1975), 1370.) Google Scholar
Chan, H. P. and Lai, T. L. (2006). Maxima of asymptotically Gaussian random fields and moderate deviation approximations to boundary crossing probabilities of sums of random variables with multidimensional indices. Ann. Prob. 34, 80121. CrossRefGoogle Scholar
Cheng, D. and Xiao, Y. (2016a). Excursion probability of Gaussian random fields on sphere. Bernoulli 22, 11131130. Google Scholar
Cheng, D. and Xiao, Y. (2016b). The mean Euler characteristic and excursion probability of Gaussian random fields with stationary increments. Ann. Appl. Prob. 26, 722759. CrossRefGoogle Scholar
Cressie, N. (1980). The asymptotic distribution of the scan statistic under uniformity. Ann. Prob. 8, 828840. Google Scholar
Dębicki, K., Hashorva, E. and Ji, L. (2016). Extremes of a class of nonhomogeneous Gaussian random fields. Ann. Prob. 44, 9841012. Google Scholar
Dębicki, K., Hashorva, E. and Soja-Kukieła, N. (2015a). Extremes of homogeneous Gaussian random fields. J. Appl. Prob. 52, 5567. Google Scholar
Dębicki, K., Hashorva, E., Ji, L. and Ling, C. (2015b). Extremes of order statistics of stationary processes. TEST 24, 229248. Google Scholar
Dębicki, K., Hashorva, E., Ji, L. and Tabiś, K. (2015c). Extremes of vector-valued Gaussian processes: exact asymptotics. Stoch. Process. Appl. 125, 40394065. Google Scholar
Deheuvels, P. and Devroye, L. (1987). Limit laws of Erdős–Rényi–Shepp type. Ann. Prob. 15, 13631386. Google Scholar
Dümbgen, L. and Spokoiny, V. G. (2001). Multiscale testing of qualitative hypotheses. Ann. Statist. 29, 124152. Google Scholar
Giné, E. and Nickl, R. (2010). Confidence bands in density estimation. Ann. Statist. 38, 11221170. Google Scholar
Giné, E., Koltchinskii, V. and Sakhanenko, L. (2004). Kernel density estimators: convergence in distribution for weighted sup-norms. Prob. Theory Relat. Fields 130, 167198. Google Scholar
Hashorva, E. and Tan, Z. (2013). Large deviations of Shepp statistics for fractional Brownian motion. Statist. Prob. Lett. 83, 22422247. Google Scholar
Hashorva, E., Ji, L. and Piterbarg, V. I. (2013). On the supremum of γ-reflected processes with fractional Brownian motion as input. Stoch. Process. Appl. 123, 41114127. Google Scholar
Hüsler, J. (1990). Extreme values and high boundary crossings for locally stationary Gaussian processes. Ann. Prob. 18, 11411158. Google Scholar
Hüsler, J. (1999). Extremes of Gaussian processes, on results of Piterbarg and Seleznjev. Statist. Prob. Lett. 44, 251258. Google Scholar
Hüsler, J. and Piterbarg, V. (2004a). On the ruin probability for physical fractional Brownian motion. Stoch. Process. Appl. 113, 315332. CrossRefGoogle Scholar
Hüsler, J. and Piterbarg, V. (2004b). Limit theorem for maximum of the storage process with fractional Brownian motion as input. Stoch. Process. Appl. 114, 231250. CrossRefGoogle Scholar
Hüsler, J., Piterbarg, V. and Seleznjev, O. (2003). On convergence of the uniform norms for Gaussian processes and linear approximation problems. Ann. Appl. Prob. 13, 16151653. CrossRefGoogle Scholar
Kabluchko, Z. (2011). Extremes of the standardized Gaussian noise. Stoch. Process. Appl. 121, 515533. Google Scholar
Konstant, D. G. and Piterbarg, V. I. (1993). Extreme values of the cyclostationary Gaussian random process. J. Appl. Prob. 30, 8297. CrossRefGoogle Scholar
Leadbetter, M. R. and Rootzén, H. (1982). Extreme value theory for continuous parameter stationary processes. Z. Wahrscheinlichkeitsth. 60, 120. Google Scholar
Leadbetter, M. R., Lindgren, G. and Rootzén, H. (1983). Extremes and Related Properties of Random Sequences and Processes. Springer, New York. Google Scholar
McCormick, W. P. (1980). Weak convergence for the maxima of stationary Gaussian processes using random normalization. Ann. Prob. 8, 483497. Google Scholar
Mittal, Y. and Ylvisaker, D. (1975). Limit distributions for the maxima of stationary Gaussian processes. Stoch. Process. Appl. 3, 118. CrossRefGoogle Scholar
Pickands, J., III. (1969). Asymptotic properties of the maximum in a stationary Gaussian process. Trans. Amer. Math. Soc. 145, 7586. Google Scholar
Piterbarg, V. I. (1996). Asymptotic Methods in the Theory of Gaussian Processes and Fields. American Mathematical Society, Providence, RI. Google Scholar
Piterbarg, V. I. (2001). Large deviations of a storage process with fractional Browanian motion as input. Extremes 4, 147164. CrossRefGoogle Scholar
Qiao, W. and Polonik, W. (2016). Theoretical analysis of nonparametric filament estimation. Ann. Statist. 44, 12691297. CrossRefGoogle Scholar
Qiao, W. and Polonik, W. (2017). Extrema of locally stationary Gaussian fields on growing manifolds. To appear in Bernoulli. Google Scholar
Seleznjev, O. V. (1991). Limit theorems for maxima and crossings of a sequence of Gaussian processes and approximation of random processes. J. Appl. Prob. 28, 1732. CrossRefGoogle Scholar
Seleznjev, O. (1996). Large deviations in the piecewise linear approximation of Gaussian processes with stationary increments. Adv. Appl. Prob. 28, 481499. Google Scholar
Sharpnack, J. and Arias-Castro, E. (2016). Exact asymptotics for the scan statistic and fast alternatives. Electron. J. Statist. 10, 26412684. Google Scholar
Shepp, L. A. (1966). Radon-Nykodým derivatives of Gaussian measures. Ann. Math. Statist. 37, 321354. (Correction: 5 (1977), 315317.) Google Scholar
Shepp, L. A. (1971). First passage time for a particular Gaussian process. Ann. Math. Statist. 42, 946951. Google Scholar
Siegmund, D. and Venkatraman, E. S. (1995). Using the generalized likelihood ratio statistic for sequential detection of a change-point. Ann. Statist. 23, 255271. Google Scholar
Tan, Z-Q. and Chen, Y. (2016). Some limit results on supremum of Shepp statistics for fractional Brownian motion. Appl. Math. J. Chinese Univ. B 31, 269282. Google Scholar
Tan, Z. and Yang, Y. (2015). Extremes of Shepp statistics for fractional Brownian motion. Sci. China Math. 58, 17791794. Google Scholar
Tan, Z.-Q., Hashorva, E. and Peng, Z. (2012). Asymptotics of maxima of strongly dependent Gaussian processes. J. Appl. Prob. 49, 11061118. Google Scholar
Zholud, D. (2008). Extremes of Shepp statistics for the Wiener process. Extremes 11, 339351. Google Scholar