Minimum distance estimator for a hyperbolic stochastic partial differentialequation

Vincent Monsan; Modeste N'zi

Applicationes Mathematicae (2000)

  • Volume: 27, Issue: 2, page 225-238
  • ISSN: 1233-7234

Abstract

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We study a minimum distance estimator in L 2 -norm for a class ofnonlinear hyperbolic stochastic partial differential equations, driven by atwo-parameter white noise. The consistency and asymptotic normality of thisestimator are established under some regularity conditions on thecoefficients. Our results are applied to the two-parameterOrnstein-Uhlenbeck process.

How to cite

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Monsan, Vincent, and N'zi, Modeste. "Minimum distance estimator for a hyperbolic stochastic partial differentialequation." Applicationes Mathematicae 27.2 (2000): 225-238. <http://eudml.org/doc/219270>.

@article{Monsan2000,
abstract = {We study a minimum distance estimator in $L_2$-norm for a class ofnonlinear hyperbolic stochastic partial differential equations, driven by atwo-parameter white noise. The consistency and asymptotic normality of thisestimator are established under some regularity conditions on thecoefficients. Our results are applied to the two-parameterOrnstein-Uhlenbeck process.},
author = {Monsan, Vincent, N'zi, Modeste},
journal = {Applicationes Mathematicae},
keywords = {random fields; stochastic partial differential equations; small noise; minimum distance estimator},
language = {eng},
number = {2},
pages = {225-238},
title = {Minimum distance estimator for a hyperbolic stochastic partial differentialequation},
url = {http://eudml.org/doc/219270},
volume = {27},
year = {2000},
}

TY - JOUR
AU - Monsan, Vincent
AU - N'zi, Modeste
TI - Minimum distance estimator for a hyperbolic stochastic partial differentialequation
JO - Applicationes Mathematicae
PY - 2000
VL - 27
IS - 2
SP - 225
EP - 238
AB - We study a minimum distance estimator in $L_2$-norm for a class ofnonlinear hyperbolic stochastic partial differential equations, driven by atwo-parameter white noise. The consistency and asymptotic normality of thisestimator are established under some regularity conditions on thecoefficients. Our results are applied to the two-parameterOrnstein-Uhlenbeck process.
LA - eng
KW - random fields; stochastic partial differential equations; small noise; minimum distance estimator
UR - http://eudml.org/doc/219270
ER -

References

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  2. H. Dietz and Y. Kutoyants (1997), A class of minimum-distanceestimators for diffusion processes with ergodic properties, Statistics and Decisions 15, 211-217. Zbl0921.62101
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  8. Y. Kutoyants (1994), Identification of Dynamical Systems with Small Noise, Kluwer, Dordrecht. Zbl0831.62058
  9. Y. Kutoyants and O. Lessi (1995), Minimum distance estimation for diffusion random fields, Publ. Inst. Statist. Univ. Paris 29, fasc. 3, 3-20. Zbl0837.62073
  10. Y. Kutoyants, A. Nercessian and P. Pilibossian (1994), On limit distribution of the minimum sup norm estimate of the parameter ofthe Ornstein-Uhlenbeck process, Romanian J. Pure Appl. Math. 39, 119-139. Zbl0813.62075
  11. Y. Kutoyants and P. Pilibossian (1994), On minimum L 1 estimate of the parameter of the Ornstein-Uhlenbeck process, Statist. Probab. Lett. 20, 117-123. Zbl0802.62081
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  13. C. Rovira and M. Sanz-Solé (1995), A nonlinear hyperbolic SPDE: Aproximations and support, in: London Math. Soc. Lecture Note Ser. 216, Cambridge Univ. Press, 241-261. Zbl0828.60042
  14. C. Rovira and M. Sanz-Solé (1996), The law of thesolution to a nonlinear hyperbolic SPDE, J. Theoret. Probab. 9, 863-901. Zbl0878.60040

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