Parameter Estimation for Multiscale Diffusions
نویسندگان
چکیده
منابع مشابه
Parameter Estimation for Multiscale Diffusions
We study the problem of parameter estimation for time-series possessing two, widely separated, characteristic time scales. The aim is to understand situations where it is desirable to fit a homogenized singlescale model to such multiscale data. We demonstrate, numerically and analytically, that if the data is sampled too finely then the parameter fit will fail, in that the correct parameters in...
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There are many applications where it is desirable to fit reduced stochastic descriptions (eg SDEs) to data. These include molecular dynamics [28], [6], atmosphere/ocean science [13], cellular biology [2] and econometrics [4]. The data arising in these problems often has a multiscale character and may not be compatible with the desired diffusion at small scales (see [8], [14], [11], [1] and [20]...
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We study the problem of parameter estimation using maximum likelihood for fast/slow systems of stochastic differential equations. Our aim is to shed light on the problem of model/data mismatch at small scales. We consider two classes of fast/slow problems for which a closed coarse-grained equation for the slow variables can be rigorously derived, which we refer to as averaging and homogenizatio...
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We construct importance sampling schemes for stochastic differential equations with small noise and fast oscillating coefficients. Standard Monte Carlo methods perform poorly for these problems in the small noise limit. With multiscale processes there are additional complications, and indeed the straightforward adaptation of methods for standard small noise diffusions will not produce efficient...
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ژورنال
عنوان ژورنال: Journal of Statistical Physics
سال: 2007
ISSN: 0022-4715,1572-9613
DOI: 10.1007/s10955-007-9300-6