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The quasi maximum likelihood approach to statistical inference on a nonstationary multivariate ARFIMA process
-
Amadou Kamagaté
und
Ouagnina Hili
Veröffentlicht/Copyright:
20. August 2013
Abstract.
We estimate the parameters of a nonstationary multivariate ARFIMA (AutoRegressive Fractionally Integrated Moving Average) process by the quasi likelihood approach. Then, we define the pseudo-spectral density of the process. Under some assumptions, we establish consistency, asymptotic normality.
Keywords: Quasi-maximum-likelihood; long memory; multivariate time series; nonstationary ARFIMA process
Received: 2011-12-15
Revised: 2012-07-22
Accepted: 2013-03-15
Published Online: 2013-08-20
Published in Print: 2013-09-01
© 2013 by Walter de Gruyter Berlin Boston
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Artikel in diesem Heft
- Masthead
- An ergodic-type theorem for generalized Ornstein–Uhlenbeck processes
- A note on Feynman–Kac path integral representations for scalar wave motions
- Mutual information for stochastic differential equation with subfractional noises
- The quasi maximum likelihood approach to statistical inference on a nonstationary multivariate ARFIMA process
Schlagwörter für diesen Artikel
Quasi-maximum-likelihood;
long memory;
multivariate time series;
nonstationary ARFIMA process
Artikel in diesem Heft
- Masthead
- An ergodic-type theorem for generalized Ornstein–Uhlenbeck processes
- A note on Feynman–Kac path integral representations for scalar wave motions
- Mutual information for stochastic differential equation with subfractional noises
- The quasi maximum likelihood approach to statistical inference on a nonstationary multivariate ARFIMA process
