A Frequency Domain Approach for the Estimation of Parameters of Spatio-Temporal Stationary Random Processes

In this paper we consider the estimation of the parameters of the spatio-temporal covariances of spatio-temporal stationary random processes. We define Finite Fourier Transforms of the processes at each location and based on joint distribution of these complex valued random variables we define an approximate likelihood function and consider the maximization. Ideas are similar to Whittle likelihood function considered in time series. The sampling properties of the estimators are investigated. The method is applied to simulated data and also to pacific wind speed data considered earlier by Cressie and Huang [6].