Computationally Ecient Stochastic Realization for Internal Multiscale Autoregressive Models*
نویسندگان
چکیده
In this paper we develop a stochastic realization theory for multiscale autoregressive (MAR) processes that leads to computationally ecient realization algorithms. The utility of MAR processes has been limited by the fact that the previously known general purpose realization algorithm, based on canonical correlations, leads to model inconsistencies and has complexity quartic in problem size. Our realization theory and algorithms addresses these issues by focusing on the estimation-theoretic concept of predictive eciency and by exploiting the scale-recursive structure of so-called internal MAR processes. Our realization algorithm has complexity quadratic in problem size and with an approximation we also obtain an algorithm that has complexity linear in problem size.
منابع مشابه
Computationally Eecient Stochastic Realization for Internal Multiscale Autoregressive Models *
In this paper we develop a stochastic realization theory for multiscale autoregressive (MAR) processes that leads to computationally eecient realization algorithms. The utility of MAR processes has been limited by the fact that the previously known general purpose realization algorithm, based on canonical correlations, leads to model inconsistencies and has complexity quartic in problem size. O...
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