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 the homog-enized model are not identified. We also show, numerically and analytically, that if the data is subsampled at an appropriate rate then it is possible to estimate the coefficients of the homogenized model correctly
We study the problem of parameter estimation using maximum likelihood for fast/slow systems of stoch...
In porous media physics, calibrating model parameters through experiments is a challenge. ...
In certain situations, observations may be made on a multivariate time series on a given temporal sc...
We study the problem of parameter estimation for time-series possessing two, widely separated, chara...
We study the problem of parameter estimation for time-series possessing two, widely separated, chara...
There are many applications where it is desirable to fit reduced stochastic descriptions (e.g. SDEs)...
International audienceThe aim of this paper is to study two-time-scale nonlinear transient models an...
International audienceThe aim here is to study two-time-scale models and their associated parameter ...
We construct a novel estimator for the diffusion coefficient of the limiting homogenized equation, w...
A process generated by a stochastic differential equation driven by pure noise is sampled at irregul...
AbstractA process generated by a stochastic differential equation driven by pure noise is sampled at...
We study the problem of drift estimation for two-scale continuous time series. We set ourselves in t...
A quasi-periodic time series is sampled at a varying but unknown rate. An autoregressive moving-aver...
Some dynamical systems are characterized by more than one timescale, e.g. two well separated time-sc...
AbstractWe study the problem of parameter estimation using maximum likelihood for fast/slow systems ...
We study the problem of parameter estimation using maximum likelihood for fast/slow systems of stoch...
In porous media physics, calibrating model parameters through experiments is a challenge. ...
In certain situations, observations may be made on a multivariate time series on a given temporal sc...
We study the problem of parameter estimation for time-series possessing two, widely separated, chara...
We study the problem of parameter estimation for time-series possessing two, widely separated, chara...
There are many applications where it is desirable to fit reduced stochastic descriptions (e.g. SDEs)...
International audienceThe aim of this paper is to study two-time-scale nonlinear transient models an...
International audienceThe aim here is to study two-time-scale models and their associated parameter ...
We construct a novel estimator for the diffusion coefficient of the limiting homogenized equation, w...
A process generated by a stochastic differential equation driven by pure noise is sampled at irregul...
AbstractA process generated by a stochastic differential equation driven by pure noise is sampled at...
We study the problem of drift estimation for two-scale continuous time series. We set ourselves in t...
A quasi-periodic time series is sampled at a varying but unknown rate. An autoregressive moving-aver...
Some dynamical systems are characterized by more than one timescale, e.g. two well separated time-sc...
AbstractWe study the problem of parameter estimation using maximum likelihood for fast/slow systems ...
We study the problem of parameter estimation using maximum likelihood for fast/slow systems of stoch...
In porous media physics, calibrating model parameters through experiments is a challenge. ...
In certain situations, observations may be made on a multivariate time series on a given temporal sc...