Adaptive filtering revisited

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Nau, RF; Oliver, RM

Published Date

  • January 1, 1979

Published In

Volume / Issue

  • 30 / 9

Start / End Page

  • 825 - 831

Electronic International Standard Serial Number (EISSN)

  • 1476-9360

International Standard Serial Number (ISSN)

  • 0160-5682

Digital Object Identifier (DOI)

  • 10.1057/jors.1979.193

Citation Source

  • Scopus