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A New Precipitable Water Vapor STARMA Model Based on Newton’s Method

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 367)

Abstract

The STARMA (space-time autoregressive moving average) model is introduced in 2002–2008 monthly PWV fitting and forecast. To enhance the model’s ability of dealing with satellite remote sensing raster data, this article extends the parameter estimation process in the STARMA model by augmenting the Newton’s method to high dimensions for solving system of nonlinear equations, and the process of parameter estimation is elaborated. This operation is validated by real data experiment results. The confirmation results of this method reveals that the STARMA model has good accuracy in both fitting and predicting.

Keywords

Space-time series modeling STARMA model Newton’s method Precipitable water vapour (PWV) 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Key Laboratory of Firefighting and Rescue Technology, MPSLangfang HebeiChina
  2. 2.Fire Engineering Department of Chinese People’s Armed Police Forces AcademyLangfangChina

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