TY - JOUR ID - 14771 TI - Analysis of Spatial-Temporal data: the Case Study of Zanjan Daily mean Wind Speed Data JO - Journal of Advanced Mathematical Modeling JA - JAMM LA - en SN - 2251-8088 AU - Shahnavaz, Ali AU - M. Mosammam, Ali AU - Behzadi, Mohammad Hassan AD - Department of Statistics. Science and Research Branch. Islamic Azad University. Tehran. Iran AD - Department of Statistics. University of Zanjan. Zanjan. Iran Y1 - 2019 PY - 2019 VL - 9 IS - 2 SP - 53 EP - 76 KW - Space-time model KW - Half-spectral model KW - Whittle likelihood DO - 10.22055/jamm.2019.26917.1624 N2 - In this paper, we first study the theory of the spatial-temporal half spectral modelling and describe some properties of recently proposed half spectral models. Next, we propose an estimation method for the estimation of spatial-temporal covariance functions in the half-spectral setting. To assess the performance of the proposed half-spectral models, we conduct two simulations. in which we compare the proposed fitting approach with respect to the other classical estimation methods. The proposed methods have great success in fitting parametric space-time covariance functions specifically for massive data sets. Finally, we apply the proposed methods for a real daily wind speed data in Zanjan, Iran. UR - https://jamm.scu.ac.ir/article_14771.html L1 - https://jamm.scu.ac.ir/article_14771_21c15c6af4c4d4a622cc3320d2e6b452.pdf ER -