Placeholder text

Go to cart

A New Approach to Forecasting

By John O'Reilly

A New Approach to Forecasting

By John O'Reilly

0 - Default Title
Description
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.
Product details
Binding:
Paperback
Number of Pages:
138
Release Date:
2025-07-28
Publication Date:
2025-07-28
Publisher:
Troubador Publishing Ltd
Languages:
Original: English
ISBN10:
1836282869
ISBN13:
9781836282860
GPSR Manufacturer Reference:
[email protected]
Weight:
323 g
Height:
156 cm
Width:
234 cm
Thickness:
9 cm
Buy on Amazon
Currently sold out