Vector Autoregressive Model-Order Selection From Finite Samples Using Kullback's Symmetric Divergence

2006 ◽  
Vol 53 (10) ◽  
pp. 2327-2335 ◽  
Author(s):  
A.-K. Seghouane
Keyword(s):  
Autoregressive Model ◽  
Order Selection ◽  
Vector Autoregressive Model ◽  
Model Order Selection ◽  
Model Order ◽  
Vector Autoregressive ◽  
Finite Samples

Modal Parameters Estimation and Model Order Selection of a Structure Excited by a Random Force

1999 ◽  
Author(s):  
N. Larbi ◽  
J. Lardies
Keyword(s):  
Maximum Likelihood ◽  
Minimum Description Length ◽  
Moving Average ◽  
Random Force ◽  
Parameters Estimation ◽  
Modal Parameters ◽  
Order Selection ◽  
Model Order Selection ◽  
Model Order ◽  
Vector Autoregressive

Abstract A multivariate maximum likelihood procedure for the estimation of modal parameters is presented. The vibrating system is excited by a random force and sensors output only are used to estimate the natural frequencies and damping coefficients of the system. The method works in time domain and a vector autoregressive moving average (VARMA) process is used. The information about modal parameters is contained in the multivariate AR part, which is estimated using an iterative maximum likelihood algorithm. This algorithm uses a score technique and output data only. The order of the AR part is obtained via the Minimum Description Length associated with an instrumental variable procedure. Experimental results show the effectiveness of the method for model order selection and modal parameters estimation.

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