A multivariate preconditioned conjugate gradient approach for maximum likelihood estimation in vector long memory processes

We present an approach via a multivariate preconditioned conjugate gradient (MPCG) algorithm for maximum likelihood estimation of parameters from vector ARFIMA models with Gaussian errors. This approach involves the solution of a block-Toeplitz system, and Monte Carlo integration over the process history.

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Year of publication:	2009
Authors:	Pai, Jeffrey ; Ravishanker, Nalini
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 79.2009, 9, p. 1282-1289
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005023185