Skip to main content
Log in

Markov-modulated Hawkes process with stepwise decay

  • Published:
Annals of the Institute of Statistical Mathematics Aims and scope Submit manuscript

Abstract

This paper proposes a new model—the Markov-modulated Hawkes process with stepwise decay (MMHPSD)—to investigate the variation in seismicity rate during a series of earthquake sequences including multiple main shocks. The MMHPSD is a self-exciting process which switches among different states, in each of which the process has distinguishable background seismicity and decay rates. Parameter estimation is developed via the expectation maximization algorithm. The model is applied to data from the Landers–Hector Mine earthquake sequence, demonstrating that it is useful for modelling changes in the temporal patterns of seismicity. The states in the model can capture the behavior of main shocks, large aftershocks, secondary aftershocks, and a period of quiescence with different background rates and decay rates.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Akaike H. (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6): 716–723

    Article  MathSciNet  MATH  Google Scholar 

  • Akaike, H. (1978). A Bayesian analysis of the minimum AIC procedure. Annals of the Institute of Statistical Mathematics, 30(1), 9–14; also included in E. Parzen et al. (Eds.) (1998), Selected papers of Hirotugu Akaike (pp. 275–280). Berlin: Springer.

  • Bebbington M.S. (2007) Identifying volcanic regimes using hidden Markov models. Geophysical Journal International, 171: 921–942

    Article  Google Scholar 

  • Bebbington M.S. (2008) Estimating rate- and state-fraction parameters using a two-node stochastic model for aftershocks. Tectonophysics, 457: 71–85

    Article  Google Scholar 

  • Bebbington M.S., Harte D.S. (2001) On the statistics of the linked stress release model. Journal of Applied Probability, 38A: 176–187

    Article  MathSciNet  MATH  Google Scholar 

  • Bebbington M.S., Harte D.S., Jaumé S.C. (2010) Repeated intermittent earthquake cycles in the San Francisco Bay Region. Pure and Applied Geophysics, 167: 801–818

    Article  Google Scholar 

  • Borovkov K., Bebbington M.S. (2003) A stochastic two-node stress transfer model reproducing Omori’s law. Pure and Applied Geophysics, 160: 1429–1445

    Article  Google Scholar 

  • Bowsher C.G. (2007) Modelling security market events in continuous time: intensity based, multivariate point process models. Journal of Econometrics, 141: 876–912

    Article  MathSciNet  Google Scholar 

  • Brémaud P., Massoulié L. (1996) Stability of nonlinear Hawkes processes. Annals of Probability, 24: 1563–1588

    Article  MathSciNet  MATH  Google Scholar 

  • Bufe C.G., Varnes D.J. (1993) Predictive modeling of the seismic cycle of the greater San Francisco Bay region. Journal of Geophysical Research, 98: 9871–9883

    Article  Google Scholar 

  • Daley D.J., Vere-Jones D. (2003) Introduction to the theory of point processes (2nd ed). Springer, New York

    MATH  Google Scholar 

  • Fedotov S.A. (1968) The seismic cycle, quantitative seismic zoning, and long-term seismic forecasting. In: Medvedev S.V. (eds) Seismic zoning in the USSR. Izdatel’stvo Nauka, Moscow, pp 133–166

    Google Scholar 

  • Fischer W., Meier-Hellstern K.S. (1993) The Markov-modulated Poisson process (MMPP) cookbook. Performance Evaluation, 18(2): 149–171

    Article  MathSciNet  MATH  Google Scholar 

  • Fletcher R., Powell M.J.D. (1963) A rapidly convergent method for minimization. The Computer Journal, 6: 163–168

    MathSciNet  MATH  Google Scholar 

  • Harte, D. S. (2005). Package “HiddenMarkov”: discrete time hidden Markov models. R statistical program routines. Wellington: Statistics Research Associates. http://cran.at.r-project.org/web/packages/HiddenMarkov.

  • Hawkes A.G. (1971) Spectra of some self-exciting and mutually exciting point processes. Biometrika, 58: 83–90

    Article  MathSciNet  MATH  Google Scholar 

  • Hawkes A.G., Adamopoulos L. (1973) Cluster models for earthquakes-regional comparisons. Bulletin of the International Statistical Institute, 45: 454–461

    Google Scholar 

  • Heffes H., Lucantoni D. (1986) A Markov modulated characterization of packetized voice and data traffic related statistical performance. IEEE Journal on Selected Areas in Communications, 4: 856–868

    Article  Google Scholar 

  • Helmstetter, A., Sornette, D. (2002). Subcritical and supercritical regimes in epidemic models of earthquake aftershocks. Journal of Geophysical Research, 107. doi:10.1029/2001JB001580

  • Hill, D. P., Reasenberg, P. A., Michael, A., Arabaz, W., Beroza, G. C., Brune, J. N., Brumbaugh, D., Davis, S., DePolo, D., Ellsworth, W. L., Gomberg, J., Harmsen, S., House, L., Jackson, S. M., Johnston, M., Jones, L., Keller, R., Malone, S., Nava, S., Pechmann, J. C., Sanford, A., Simpson, R. W., Smith, R. S., Stark, M., Stickney, M., Walter, S., Zollweg, J. (1993). Seismicity in the western United States remotely triggered by the M7.4 Landers, California, earthquake of June 28, 1992. Science, 260, 1617–1623.

    Google Scholar 

  • Hill D.P., Johnston M.J.S., Langbein J.O., Bilham R. (1995) Response of Long Valley caldera to the M w  = 7.3 Landers, California, earthquake. Journal of Geophysical Research, 100: 12985–13005

    Article  Google Scholar 

  • Hughes J.P., Guttorp P. (1994) A class of stochastic models for relating synoptic atmospheric patterns to regional hydrologic phenomena. Water Resources Research, 30: 1535–1546

    Article  Google Scholar 

  • Jaumé, S. C., Bebbington, M. S. (2004). Accelerating seismic release from a self-correcting stochastic model. Journal of Geophysical Research, 109, B12301. doi:10.1029/2003JB002867

  • MacDonald I., Zucchini W. (1997) Hidden-Markov and other models for discrete-valued time series. Chapman and Hall, New York

    MATH  Google Scholar 

  • Marsan D. (2003) Triggering of seismicity at short timescales following Californian earthquakes. Journal of Geophysical Research, 108: 2266. doi:10.1029/2002JB001946

    Article  Google Scholar 

  • Marsan D., Nalbant S.S. (2005) Methods for measuring seismicity rate changes: a review and a study of how the M w 7.3 Landers earthquake affected the aftershock sequence of the M w 6.1 Joshua Tree earthquake. Pure and Applied Geophysics, 162: 1151–1185

    Article  Google Scholar 

  • Mogi K. (1968) Source locations of elastic shocks in the fracturing process in rocks (1). Bulletin of Earthquake Research Institute, 46: 1103–1125

    Google Scholar 

  • Ogata Y. (1988) Statistical models for earthquake occurrences and residual analysis for point processes. Journal of the American Statistical Association, 83(401): 9–27

    Article  Google Scholar 

  • Ogata Y. (1998) Space-time point-process models for earthquake occurrences. Annals of the Institute of Statistical Mathematics, 50: 379–402

    Article  MATH  Google Scholar 

  • Ogata, Y., Jones, L. M., Toda, S. (2003). When and where the aftershock activity was depressed: contrasting decay patterns of the proximate large earthquakes in southern California. Journal of Geophysical Research, 108(B6), 2318. doi:10.1029/2002JB002009 (ESE1-12).

  • Pievatolo A., Rotondi R. (2008) Statistical identification of seismic phases. Geophysical Journal International, 173: 942–957

    Article  Google Scholar 

  • Rabiner L.R. (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77: 257–286

    Article  Google Scholar 

  • Roberts W.J.J., Ephraim Y., Dieguez E. (2006) On Rydén’s EM algorithm for estimating MMPPs. IEEE Signal Processing Letters, 13(6): 373–376

    Article  Google Scholar 

  • Rydén T. (1994) Parameter estimation for Markov modulated Poisson processes. Communications in Statistics–Stochastic Models, 10(4): 795–829

    Article  MathSciNet  MATH  Google Scholar 

  • Rydén T. (1996) An EM algorithm for estimation in Markov-modulated Poisson processes. Computational Statistics & Data Analysis, 21: 431–447

    Article  MathSciNet  MATH  Google Scholar 

  • Schwarz G. (1978) Estimating the dimension of a model. Annals of Statistics, 6: 461–464

    Article  MathSciNet  MATH  Google Scholar 

  • Shibata R. (1980) Asymptotically efficient selection of the order of the model for estimating parameters of a linear process. The Annals of Statistics, 8: 147–164

    Article  MathSciNet  MATH  Google Scholar 

  • Shibata R. (1981) An optimal selection of regression variables. Biometrika, 68(1): 45–54

    Article  MathSciNet  MATH  Google Scholar 

  • Utsu T., Ogata Y., Matsu’ura R.S. (1995) The centenary of the Omori formula for a decay law of aftershock activity. Journal of Physics of the Earth, 43: 1–33

    Article  Google Scholar 

  • Van Loan C.F. (1978) Computing integrals involving the matrix exponential. IEEE Transactions on Automatic Control, AC- 23(3): 395–404

    Article  MATH  Google Scholar 

  • Vere-Jones D., Robinson R., Yang W. (2001) Remarks on the accelerated moment release model: problems of model formulation, simulation and estimation. Geophysical Journal International, 144: 517–531

    Article  Google Scholar 

  • Wang, T. (2010). Statistical models for earthquakes incorporating ancillary data. PhD thesis, New Zealand: Massey University.

  • Zhuang J. (2000) Statistical modeling of seismicity patterns before and after the 1990 Oct 5 Cape Palliser earthquake, New Zealand. New Zealand Journal of Geology and Geophysics, 43: 447–460

    Article  Google Scholar 

  • Zucchini W., Guttorp P. (1991) A hidden Markov model for space-time precipitation. Water Resources Research, 27(8): 1917–1923

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ting Wang.

About this article

Cite this article

Wang, T., Bebbington, M. & Harte, D. Markov-modulated Hawkes process with stepwise decay. Ann Inst Stat Math 64, 521–544 (2012). https://doi.org/10.1007/s10463-010-0320-7

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10463-010-0320-7

Keywords

Navigation