Displaying similar documents to “Minimum distance estimator for a hyperbolic stochastic partial differentialequation”

On a strongly consistent estimator of the squared L_2-norm of a function

Roman Różański (1995)

Applicationes Mathematicae

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A kernel estimator of the squared L 2 -norm of the intensity function of a Poisson random field is defined. It is proved that the estimator is asymptotically unbiased and strongly consistent. The problem of estimating the squared L 2 -norm of a function disturbed by a Wiener random field is also considered.

Quasi-Likelihood Estimation for Ornstein-Uhlenbeck Diffusion Observed at Random Time Points

Adès, Michel, Dion, Jean-Pierre, MacGibbon, Brenda (2005)

Serdica Mathematical Journal

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2000 Mathematics Subject Classification: 60J60, 62M99. In this paper, we study the quasi-likelihood estimator of the drift parameter θ in the Ornstein-Uhlenbeck diffusion process, when the process is observed at random time points, which are assumed to be unobservable. These time points are arrival times of a Poisson process with known rate. The asymptotic properties of the quasi-likelihood estimator (QLE) of θ, as well as those of its approximations are also elucidated....

Ergodicity of increments of the Rosenblatt process and some consequences

Petr Čoupek, Pavel Křížek, Bohdan Maslowski (2025)

Czechoslovak Mathematical Journal

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A new proof of the mixing property of the increments of Rosenblatt processes is given. The proof relies on infinite divisibility of the Rosenblatt law that allows to prove only the pointwise convergence of characteristic functions. Subsequently, the result is used to prove weak consistency of an estimator for the self-similarity parameter of a Rosenblatt process, and to prove the existence of a random attractor for a random dynamical system induced by a stochastic reaction-diffusion...

Second-order asymptotic expansion for a non-synchronous covariation estimator

Arnak Dalalyan, Nakahiro Yoshida (2011)

Annales de l'I.H.P. Probabilités et statistiques

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In this paper, we consider the problem of estimating the covariation of two diffusion processes when observations are subject to non-synchronicity. Building on recent papers [ (2005) 359–379, (2008) 367–406], we derive second-order asymptotic expansions for the distribution of the Hayashi–Yoshida estimator in a fairly general setup including random sampling schemes and non-anticipative random drifts. The key steps leading to our results are a second-order...