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Maximum likelihood estimation in vector long memory processes via EM algorithm
Authors:Jeffrey Pai  Nalini Ravishanker  
Affiliation:aWarren Centre of Actuarial Studies and Research, University of Manitoba, Winnipeg, Manitoba R3T 5V4, Canada;bDepartment of Statistics, University of Connecticut, Storrs, CT 06269, USA
Abstract:We present an approach for exact maximum likelihood estimation of parameters from univariate and multivariate autoregressive fractionally integrated moving average models with Gaussian errors using the Expectation Maximization (EM) algorithm. The method takes advantage of the relation between the VARFIMA(0,d,0) process and the corresponding VARFIMA(p,d,q) process in the computation of the likelihood.
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