Hostname: page-component-745bb68f8f-5r2nc Total loading time: 0 Render date: 2025-01-09T18:59:09.927Z Has data issue: false hasContentIssue false
  • English
  • Français

Identification and estimation of dynamic space-time forecasting models

Published online by Cambridge University Press:  01 July 2016

Ronald Martin
Ronald Martin*
Affiliation:
University of Cambridge
Get access Rights & Permissions [Opens in a new window]

Extract

This paper is concerned with the identification and estimation of dynamic space-time models for the evolution of a single random variable Y across space and through time. Suppose Y takes on values yit for each geographic zone i = 1, …, n in successive time periods t = 1, …, T.

Type
Applications of Spatial Models
Information
Advances in Applied Probability , Volume 7 , Issue 3 , September 1975 , pp. 455 - 456
Copyright
Copyright © Applied Probability Trust 1975 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Cliff, A. D. and Ord, J. K. (1973) Spatial Autocorrelation. Pion, London.Google Scholar
Martin, R. L. and Oeppen, J. E. (1974) Identification of Space-Time Forecasting Models for Geographical Research. To appear.Google Scholar
Panuska, V. (1969) An adaptive recursive least squares identification algorithm. I.E.E.E. Proc. 8th Symp. Adaptive Processes. CrossRefGoogle Scholar