Volume 5, Issue 3
Space-Time Arima Modeling for Regional Precipitation Forecasting

Kazimierz Adamowski, Nicolas R. Dalezios & Fadil Bmohamed

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J. Comp. Math., 5 (1987), pp. 249-263

Published online: 1987-05

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  • Abstract

An aggregate regional forecasting model class belonging to the general family of space-time auto regressive moving average process is investigated. these models are characterised by autoregressive and moving average terms lagged in both time and space. the paper demonstrates an iterative procedure for buling a starima model of precipitation time series. eleven rainage sites locaated in a watershed in southern Ontario, Canada, sampled at 15-day intervals for the period of 1966 to 1980 are used in the numerical analysis. The identified model is stma($l_2)$. the model parameters are estimated by the polytope technique, a nonlinear optimization algorithm. the developed model performed well in regional forecasting and in describing the spatio-temporal characteristics of the precipitation time series.

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@Article{JCM-5-249, author = {Kazimierz Adamowski, Nicolas R. Dalezios and Fadil Bmohamed}, title = {Space-Time Arima Modeling for Regional Precipitation Forecasting}, journal = {Journal of Computational Mathematics}, year = {1987}, volume = {5}, number = {3}, pages = {249--263}, abstract = { An aggregate regional forecasting model class belonging to the general family of space-time auto regressive moving average process is investigated. these models are characterised by autoregressive and moving average terms lagged in both time and space. the paper demonstrates an iterative procedure for buling a starima model of precipitation time series. eleven rainage sites locaated in a watershed in southern Ontario, Canada, sampled at 15-day intervals for the period of 1966 to 1980 are used in the numerical analysis. The identified model is stma($l_2)$. the model parameters are estimated by the polytope technique, a nonlinear optimization algorithm. the developed model performed well in regional forecasting and in describing the spatio-temporal characteristics of the precipitation time series. }, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/9548.html} }
TY - JOUR T1 - Space-Time Arima Modeling for Regional Precipitation Forecasting AU - Kazimierz Adamowski, Nicolas R. Dalezios & Fadil Bmohamed JO - Journal of Computational Mathematics VL - 3 SP - 249 EP - 263 PY - 1987 DA - 1987/05 SN - 5 DO - http://dor.org/ UR - https://global-sci.org/intro/article_detail/jcm/9548.html KW - AB - An aggregate regional forecasting model class belonging to the general family of space-time auto regressive moving average process is investigated. these models are characterised by autoregressive and moving average terms lagged in both time and space. the paper demonstrates an iterative procedure for buling a starima model of precipitation time series. eleven rainage sites locaated in a watershed in southern Ontario, Canada, sampled at 15-day intervals for the period of 1966 to 1980 are used in the numerical analysis. The identified model is stma($l_2)$. the model parameters are estimated by the polytope technique, a nonlinear optimization algorithm. the developed model performed well in regional forecasting and in describing the spatio-temporal characteristics of the precipitation time series.
Kazimierz Adamowski, Nicolas R. Dalezios & Fadil Bmohamed. (1970). Space-Time Arima Modeling for Regional Precipitation Forecasting. Journal of Computational Mathematics. 5 (3). 249-263. doi:
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