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Statistical analysis of the inhomogeneous telegrapher's process

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  • Iacus, Stefano Maria

Abstract

We consider a problem of estimation for the telegrapher's process on the line, say X(t), driven by a Poisson process with non-constant rate. The finite-dimensional law of the process X(t) is a solution to the telegraph equation with non-constant coefficients. We present the explicit law (P[theta]) of the process X(t) for a parametric class of intensity functions for the Poisson process. This is one rare example where an explicit law can be obtained. We propose further, an estimator for the parameter [theta] of P[theta] and we discuss its properties as a first attempt to apply statistics to these models.

Suggested Citation

  • Iacus, Stefano Maria, 2001. "Statistical analysis of the inhomogeneous telegrapher's process," Statistics & Probability Letters, Elsevier, vol. 55(1), pages 83-88, November.
    • Handle: RePEc:eee:stapro:v:55:y:2001:i:1:p:83-88
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    References listed on IDEAS

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    1. Foong, S. K. & Kanno, S., 1994. "Properties of the telegrapher's random process with or without a trap," Stochastic Processes and their Applications, Elsevier, vol. 53(1), pages 147-173, September.
    2. Orsingher, Enzo, 1985. "Hyperbolic equations arising in random models," Stochastic Processes and their Applications, Elsevier, vol. 21(1), pages 93-106, December.
    3. Orsingher, Enzo, 1990. "Probability law, flow function, maximum distribution of wave-governed random motions and their connections with Kirchoff's laws," Stochastic Processes and their Applications, Elsevier, vol. 34(1), pages 49-66, February.
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    Cited by:

    1. De Gregorio, Alessandro & Macci, Claudio, 2012. "Large deviation principles for telegraph processes," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 1874-1882.
    2. De Gregorio, Alessandro & Iafrate, Francesco, 2021. "Telegraph random evolutions on a circle," Stochastic Processes and their Applications, Elsevier, vol. 141(C), pages 79-108.
    3. De Gregorio, Alessandro, 2009. "Parametric estimation for planar random flights," Statistics & Probability Letters, Elsevier, vol. 79(20), pages 2193-2199, October.
    4. M. Consuelo Casabán & Rafael Company & Lucas Jódar, 2019. "Numerical Integral Transform Methods for Random Hyperbolic Models with a Finite Degree of Randomness," Mathematics, MDPI, vol. 7(9), pages 1-21, September.
    5. Johan GB Beumee & Chris Cormack & Peyman Khorsand & Manish Patel, 2014. "Path Diffusion, Part I," Papers 1406.0077, arXiv.org.
    6. Macci, Claudio, 2016. "Large deviations for some non-standard telegraph processes," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 119-127.
    7. Nicole Bauerle & Igor Gilitschenski & Uwe D. Hanebeck, 2014. "Exact and Approximate Hidden Markov Chain Filters Based on Discrete Observations," Papers 1411.0849, arXiv.org, revised Dec 2014.

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