Hostname: page-component-848d4c4894-cjp7w Total loading time: 0 Render date: 2024-06-14T22:31:50.914Z Has data issue: false hasContentIssue false

On the Density Functions of Integrals of Gaussian Random Fields

Published online by Cambridge University Press:  22 February 2016

Jingchen Liu*
Affiliation:
Columbia University
Gongjun Xu*
Affiliation:
Columbia University
*
Postal address: Department of Statistics, Columbia University, 1255 Amsterdam Avenue, New York, NY 10027, USA.
Postal address: Department of Statistics, Columbia University, 1255 Amsterdam Avenue, New York, NY 10027, USA.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In the paper we consider the density functions of random variables that can be written as integrals of exponential functions of Gaussian random fields. In particular, we provide closed-form asymptotic bounds for the density functions and, under smoothness conditions, we derive exact tail approximations of the density functions.

Type
General Applied Probability
Copyright
© Applied Probability Trust 

References

Adler, R. J. and Taylor, J. E. (2007). Random Fields and Geometry. Springer, New York.Google Scholar
Adler, R. J., Blanchet, J. H. and Liu, J. (2012). Efficient Monte Carlo for high excursions of Gaussian random fields. Ann. Appl. Prob. 22, 11671214.Google Scholar
Asmussen, S. and Rojas-Nandayapa, L. (2008). Asymptotics of sums of lognormal random variables with Gaussian copula. Statist. Prob. Lett. 78, 27092714.CrossRefGoogle Scholar
Azais, J.-M. and Wschebor, M. (2008). A general expression for the distribution of the maximum of a Gaussian field and the approximation of the tail. Stoch. Process. Appl. 118, 11901218.CrossRefGoogle Scholar
Blanchet, J., Juneja, J. and Rojas-Nandayapa, L. (2013). Efficient tail estimation for sums of correlated lognormals. To appear in Ann. Operat. Res. Google Scholar
Bogachev, V. I. (1998). Gaussian Measures (Math. Surveys Monogr. 62). American Mathematical Society, Providence, RI.Google Scholar
Borell, C. (1975). The Brunn-Minkowski inequality in Gauss space. Invent. Math. 30, 207216.Google Scholar
Davis, R. A., Dunsmuir, W. T. M. and Wang, Y. (2000). On autocorrelation in a Poisson regression model. Biometrika 87, 491505.CrossRefGoogle Scholar
Duffie, D. and Pan, J. (1997). An overview of value at risk. J. Derivatives 4, 749.Google Scholar
Dufresne, D. (2001). The integral of geometric Brownian motion. Adv. Appl. Prob. 33, 223241.Google Scholar
Foss, S. and Richards, A. (2010). On sums of conditionally independent subexponential random variables. Math. Operat. Res. 35, 102119.Google Scholar
Landau, H. J. and Shepp, L. A. (1970). On the supremum of a Gaussian process. Sankhyā A 32, 369378.Google Scholar
Liu, J. (2012). Tail approximations of integrals of Gaussian random fields. Ann. Prob. 40, 10691104.Google Scholar
Liu, J. and Xu, G. (2012). Some asymptotic results of Gaussian random fields with varying mean functions and the associated processes. Ann. Statist. 40, 262293.Google Scholar
Mitra, A. and Resnick, S. I. (2009). Aggregation of rapidly varying risks and asymptotic independence. Adv. Appl. Prob. 41, 797828.Google Scholar
Piterbarg, V. I. (1996). Asymptotic Methods in the Theory of Gaussian Processes and Fields. American Mathematical Society, Providence, RI.Google Scholar
Sudakov, V. N. and Tsirel'son, B. S. (1974). Extremal properties of half-spaces for spherically invariant measures. Zap. Nauchn. Sem. LOMI 41, 1424.Google Scholar
Sun, J. Y. (1993). Tail probabilities of the maxima of Gaussian random fields. Ann. Prob. 21, 3471.Google Scholar
Taylor, J. E. and Adler, R. J. (2003). Euler characteristics for Gaussian fields on manifolds. Ann. Prob. 31, 533563.Google Scholar
Tsirel'son, V. S. (1975). The density of the distribution of the maximum of a Gaussian process. Theory Prob. Appl. 20, 847856.Google Scholar
Tsirel'son, B. S., Ibragimov, I. A. and Sudakov, V. N. (1976). Norms of Gaussian sample functions. In Proc. 3rd Japan-USSR Symp. on Probability Theory (Tashkent, 1975; Lecture Notes Math. 550), Springer, Berlin, pp. 2041.Google Scholar
Yor, M. (1992). On some exponential functionals of Brownian motion. Adv. Appl. Prob. 24, 509531.Google Scholar