Digital Library
Close Browse articles from a journal
 
<< previous    next >>
     Journal description
       All volumes of the corresponding journal
         All issues of the corresponding volume
           All articles of the corresponding issues
                                       Details for article 13 of 26 found articles
 
 
  Numerical computation of asymptotic covariance matrix of the gaussian estimators for vector arrla models
 
 
Title: Numerical computation of asymptotic covariance matrix of the gaussian estimators for vector arrla models
Author: Salau, M.O.
Appeared in: Communications in statistics
Paging: Volume 26 (1997) nr. 1 pages 173-192
Year: 1997
Contents: This paper proposes a simple numerical procedure for evaluating the asymptotic covariance matrix of the conditional Gaussian maximum likelihood estimator of the parameters for vector autoregressive moving average models when such models are in their appropriate echelon canonical forms. Furthermore, in the process of evaluating the covariance matrix, closed form expressions for the gradient vector are derived in relatively simple terms. Evidence is presented to illustrate the practical application of the technique. Suggestions as to the numerical implementation of the technique in finite sample situations are also made.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 13 of 26 found articles
 
<< previous    next >>
 
 Koninklijke Bibliotheek - National Library of the Netherlands