Structural Time Series Analyser, Modeller and Predictor

by Siem Jan Koopman, Andrew C. Harvey, Jurgen A. Doornik

Stamp is a package designed to model and forecast time series. It is based on structural time series models. These models use advanced techniques, such as Kalman filtering, but are set up so as to be easy to use -- at the most basic level all that is required is some appreciation of the concepts of trend, seasonal and irregular. The hard work is done by the program, leaving the user free to concentrate on formulating models and using them to make forecast. The major innovation in this new release of Stamp is the ability to estimate and forecast with multivariate models. These models may include explanatory variables as well as stochastic trend, seasonal and cyclical components. It is possible to formulate models with common trends and co-integration.

408 pages, Paperback