Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Papavasiliou, Anastasia"'
Most real-world systems exhibit a multiscale behaviour that needs to be taken into consideration when fitting the effective dynamics to data sampled at a given scale. In the case of stochastic multiscale systems driven by Brownian motion, it has been
Externí odkaz:
http://arxiv.org/abs/2407.09703
We study the problem of constructing the control driving a controlled differential equation from discrete observations of the response. By restricting the control to the space of piecewise linear paths, we identify the assumptions that ensure uniquen
Externí odkaz:
http://arxiv.org/abs/2201.10300
We construct a novel estimator for the diffusion coefficient of the limiting homogenized equation, when observing the slow dynamics of a multiscale model, in the case when the slow dynamics are of bounded variation. Previous research suggests subsamp
Externí odkaz:
http://arxiv.org/abs/1807.00915
The paper is split in two parts: in the first part, we construct the exact likelihood for a discretely observed rough differential equation, driven by a piecewise linear path. In the second part, we use this likelihood in order to construct an approx
Externí odkaz:
http://arxiv.org/abs/1612.02536
The solution of a (stochastic) differential equation can be locally approximated by a (stochastic) expansion. If the vector field of the differential equation is a polynomial, the corresponding expansion is a linear combination of iterated integrals
Externí odkaz:
http://arxiv.org/abs/1009.5556
Autor:
Papavasiliou, Anastasia
We study the problem of estimating parameters of the limiting equation of a multiscale diffusion in the case of averaging and homogenization, given data from the corresponding multiscale system. First, we review some recent results that make use of t
Externí odkaz:
http://arxiv.org/abs/1002.3241
Publikováno v:
Annals of Statistics 2011, Vol. 39, No. 4, 2047-2073
We construct the "expected signature matching" estimator for differential equations driven by rough paths and we prove its consistency and asymptotic normality. We use it to estimate parameters of a diffusion and a fractional diffusions, that is, a d
Externí odkaz:
http://arxiv.org/abs/0812.3102
Autor:
Papavasiliou, Anastasia
We consider multiscale stochastic systems that are partially observed at discrete points of the slow time scale. We introduce a particle filter that takes advantage of the multiscale structure of the system to efficiently approximate the optimal filt
Externí odkaz:
http://arxiv.org/abs/0710.5098
Autor:
Papavasiliou, Anastasia
In this paper, we study the problem of estimating a Markov chain $X$(signal) from its noisy partial information $Y$, when the transition probability kernel depends on some unknown parameters. Our goal is to compute the conditional distribution proces
Externí odkaz:
http://arxiv.org/abs/math/0210031
Publikováno v:
The Annals of Statistics, 2011 Aug 01. 39(4), 2047-2073.
Externí odkaz:
https://www.jstor.org/stable/23033592
