A New Approach to Forecasting

Professor O'Reilly brings a lifetime’s engineering experience, and not a little scholarship, to an enduring problem.

The greatest original work on forecasting ever published. By a master of the post-Kalman era. Professor O'Reilly brings a lifetime’s engineering experience, and not a little scholarship, to an enduring problem. The result: a completely new theory of filtering and prediction for causal dynamical system models subject to significant disturbance uncertainty. Any causal dynamical system model can be used.

No a priori knowledge of the model uncertainties is required. Estimation of uncertain dynamical systems, it turns out, is a modelling problem. With necessary model validation. The criterion for high-fidelity signal reconstruction is how closely the signal estimates resemble the measured output data of the actual dynamical system.

In contradistinction to the Kalman off-line nominal design approach, the causal estimation approach is an on-line model tuning approach. This physical approach places estimation of dynamical systems on an experimental footing, akin to classical physics and engineering. And closer to present day industrial practice. Both causal and Kalman approaches are evaluated within twentieth century filtering and prediction theory. The new estimator is completely general, non-statistical, and very easy to use.

UK Delivery:

• Free delivery on all orders of £10 or more.
• £1.49 delivery fee on orders below £10.
• UK orders are shipped via Royal Mail 2nd Class.

International Delivery:

• Flat rate delivery charges vary by country.

Dispatch and Delivery Times:

• All orders are shipped from our warehouse in Northampton, UK within 48 hours of receipt during working hours.
• UK mainland orders typically arrive within 3-5 working days via Royal Mail 2nd Class.
• International estimated delivery times:
• Europe & Channel Islands: 7 to 10 working days
• USA: 7 to 15 working days
• Rest of the World: 9 to 21 working days

View our full delivery infomation here.