Maximum Likelihood Estimation of Vector Autoregressive Moving Average Models.
CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF STATISTICS
Pagination or Media Count:
A method is presented for the estimation of the parameters in the vector autoregressive moving average time series model. The estimation procedure is derived from the maximum likelihood approach and is based on Newton-Raphson techniques applied to the likelihood equations. The resulting two-step Newton-Raphson procedure is computationally simple, involving only generalized least squares estimation in the second step. This Newton-Raphson estimator is shown to be asymptotically efficient and to possess a limiting multivariate normal distribution. Author
- Statistics and Probability
- Operations Research