Computation of the Fisher information matrix for time series models
The Fisher information matrix is an important tool for evaluating the accuracy of estimators. The paper is concerned with algorithmic aspects related to the computation of that matrix either asymptotically or exactly for several time series models. These models include a stationary Gaussian autoregressive moving average (ARMA), a seasonal model, the single-input-single-output model (SISO), and a vector ARMA model. After a review of the literature on the subject, several recent methods are described and compared from the point of view of complexity, accuracy, and the class of models for which they can be used.
scientific article; zbMATH DE number 903537
scientific article