Computational modeling of multivariable non-stationary time series in the state space by the AOKI_VAR algorithm

Abstract:

In this work we propose an iterative e algorithm for identification in the state space of multivariable non-stationary discrete time series considering and implementing a computational process which we will call AOKI_VAR. The proposed algorithm is based on an algorithm proposed by Masanao Aoki for computational modeling of time series. A modeling example is presented as well as discussions on validation, pbkp_rediction and modeling of time series.

Año de publicación:

2010

Keywords:

• Time variant identification
• Non-stationary time series
• Non stationary stochastic process
• Computational modeling

Fuente:

scopus