Adaptive filtering revisited
- Author(s): Nau, RF
- Oliver, RM
- et al.
Published Web Locationhttps://doi.org/10.1057/jors.1979.193
This paper shows that the adaptive filtering and forecasting techniques proposed by Makridakis and Wheelwright can be viewed as approximations to a more precise filtering method in which the Kalman filter is applied to a dynamic autoregressive model which is a special case of the models of Harrison and Stevens. The correct “learning” or “training factors” are shown to be data-dependent matrices rather than scalar constants. © 1979 Operational Research Society Ltd.