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of 28
pro vyhledávání: '"Loukianov, Oleg"'
For Sina\"i's walk (X_k) we show that the empirical measure of the environment seen from the particle (\bar\w_k) converges in law to some random measure S. This limit measure is explicitly given in terms of the infinite valley, which construction goe
Externí odkaz:
http://arxiv.org/abs/2209.00101
Publikováno v:
In Stochastic Processes and their Applications February 2024 168
We consider a one-dimensional recurrent random walk in random environment (RWRE) when the environment is i.i.d. with a parametric, finitely supported distribution. Based on a single observation of the path, we provide a maximum likelihood estimation
Externí odkaz:
http://arxiv.org/abs/1404.2551
Publikováno v:
Stochastic Processes and their Applications 124, 1 (2014) 268-288
We consider a one dimensional ballistic random walk evolving in an i.i.d. parametric random environment. We provide a maximum likelihood estimation procedure of the environment parameters based on a single observation of the path till the time it rea
Externí odkaz:
http://arxiv.org/abs/1210.6328
Let $X$ be a $\mu$-symmetric Hunt process on a LCCB space E. For an open set G $\subseteq$ E, let $\tau_G$ be the exit time of $X$ from G and $A^G$ be the generator of the process killed when it leaves G. Let $r:[0,\infty[\to[0,\infty[$ and $R (t) =
Externí odkaz:
http://arxiv.org/abs/1103.4622
Let $X$ be a one dimensional positive recurrent diffusion with initial distribution $\nu$ and invariant probability $\mu$. Suppose that for some $p> 1$, $\exists a\in\R$ such that $\forall x\in\R, \E_x T_a^p<\infty$ and $\E_\nu T_a^{p/2}<\infty$, whe
Externí odkaz:
http://arxiv.org/abs/0903.2405
Publikováno v:
In Stochastic Processes and their Applications November 2016 126(11):3578-3604
Publikováno v:
In Stochastic Processes and their Applications January 2014 124(1):268-288
Publikováno v:
ESAIM: Probability and Statistics
ESAIM: Probability and Statistics, EDP Sciences, 2011, 15, pp.197--216. ⟨10.1051/ps/2009016⟩
ESAIM: Probability and Statistics, EDP Sciences, 2011, 15, pp.197--216. ⟨10.1051/ps/2009016⟩
International audience; Let $X$ be a one dimensional positive recurrent diffusion observed in continuous time. Without assuming strict stationarity of the process, we propose a nonparametric estimator of the drift function obtained by penalization. O
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::f7806b04ade0753a7de8392c8d59861e
https://hal.archives-ouvertes.fr/hal-00367993
https://hal.archives-ouvertes.fr/hal-00367993
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