Hostname: page-component-8448b6f56d-xtgtn Total loading time: 0 Render date: 2024-04-25T06:01:41.640Z Has data issue: false hasContentIssue false

CROSSREG — A Technique for First Passage and Wave Density Analysis

Published online by Cambridge University Press:  27 July 2009

Igor Rychlik
Affiliation:
Department of Mathematical Statistics, Lund University, Box 118, S-221 00, Lund, Sweden
Georg Lindgren
Affiliation:
Department of Mathematical Statistics, Lund University, Box 118, S-221 00, Lund, Sweden

Abstract

The density of the first passage time in a nonstationary Gaussian process with random mean function can be approximated with arbitrary accuracy from a regression-type expansion. CROSSREG is a package of FORTRAN subroutines that perform intelligent transformations and numerical integrations to produce high-accuracy approximations with a minimum of computer time. The basic routines, collected in the unit ONEREG, give the density of the crossing time of a general bound. An additional set of routines make up the unit TWOREG, which also gives the bivariate density of the crossing time and the value of an accompanying process at the time of the crossing. These routines can be used to find the wavelength and amplitude density in any stationary Gaussian process. ONEREG and TWOREG are special cases of a routine MREG, which is the main routine in CROSSREG.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1993

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.Abrahams, J. (1986). A survey of recent progress on level crossing problems for random processes. In Blake, I.F. & Poor, H.V. (eds.), Communications and networks, a survey of recent advances. New York: Springer-Verlag, pp. 625.CrossRefGoogle Scholar
2.Abramowitz, M. & Stegun, I.A. (1968). Handbook of mathematical functions. Washington, DC: National Bureau of Standards.Google Scholar
3.Ditlevsen, O. (1985). Survey on applications of Slepian model processes in structural reliability. In Konishi, I., Ang, A.H.-S., & Shinozuka, M., Proceedings ICOSSAR '85, Vol. 1. Japan: IASSAR, pp. 241250.Google Scholar
4.Ditlevsen, O. & Lindgren, G. (1988). Empty envelope excursions in stationary Gaussian processes. Journal of Sound and Vibration 122: 571587.CrossRefGoogle Scholar
5.Jogréus, C. (1990). Methods for the analysis of switching stochastic systems. Ph.D. dissertation, Department of Mathematical Statistics, Lund University, Lund.Google Scholar
6.Leadbetter, M.R., Lindgren, G., & Rootzén, H. (1983). Extremes and related properties of random sequences and processes. New York: Springer-Verlag.CrossRefGoogle Scholar
7.Lindgren, G. (1983). On the shape and duration of FM-clicks. IEEE Transactions on Information Theory IT-29: 536543.CrossRefGoogle Scholar
8.Lindgren, G. & Rootzén, H. (1987). Extreme values: Theory and technical applications. Scandinavian Journal of Statistics 14: 241279.Google Scholar
9.Lindgren, G. & Rychlik, I. (1991). Slepian models and regression approximations in crossing and extreme value theory. International Statistical Review 59: 195225.CrossRefGoogle Scholar
10.Rychlik, I. (1987). Regression approximations of wavelength and amplitude distributions. Advances in Applied Probability 19: 396430.CrossRefGoogle Scholar
11.Rychlik, I. (1988). Rain flow cycle distribution for ergodic load processes. SIAM Journal of Applied Mathematics 48: 662679.CrossRefGoogle Scholar
12.Rychlik, I. (1989). On the distribution of random waves and cycles. Springer Lecture Notes in Statistics, No. 51, Extreme value theory, pp. 100113.CrossRefGoogle Scholar
13.Rychlik, I. (1990). New bounds for the first passage, wave-length and amplitude densities. Stochastic Processes and Their Applications 34: 313339.CrossRefGoogle Scholar
14.Rychlik, I. (1992). Confidence bands for linear regressions. Communications in Statistics 21: 333352.CrossRefGoogle Scholar
15.Rychlik, I. (1992). The two barriers problem for continuously differentiable processes. Advances in Applied Probability 24: 7194.CrossRefGoogle Scholar
16.Rychlik, I. & Grigoriu, M. (1992). Reliability of Daniels system with equal load sharing rule subject to stationary Gaussian dynamic loads. Probabilistic Engineering Mechanics 7: 113122.CrossRefGoogle Scholar