A FREQUENCY DOMAIN APPROACH FOR THE ESTIMATION OF PARAMETERS OF SPATIO‐TEMPORAL STATIONARY RANDOM PROCESSES†. (28th March 2014)

• Record Type: Journal Article
• Authors: Rao, Tata Subba; Das, Sourav; Boshnakov, Georgi N.
• Is Part Of: Journal of time series analysis. Volume 35:Number 4(2014:Jul.)
• Page Start: 357
• Page End: 377
• Publication Date: 2014-03-28
• Subjects: Time-series analysis -- Periodicals; 519.232
• DOI: 10.1111/jtsa.12069
• Languages: English
• ISSNs: 0143-9782

Abstract

<abstract abstract-type="main" id="jtsa12069-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="jtsa12069-para-0002">A frequency domain methodology is proposed for estimating parameters of covariance functions of stationary spatio‐temporal processes. Finite Fourier transforms of the processes are defined at each location. Based on the joint distribution of these complex valued random variables, an approximate likelihood function is constructed. The sampling properties of the estimators are investigated. It is observed that the expectation of these transforms can be considered to be a frequency domain analogue of the classical variogram. We call this measure frequency variogram. The method is applied to simulated data and also to Pacific wind speed data considered earlier by Cressie and Huang (1999). The proposed method does not depend on the distributional assumptions about the process.</p> </abstract>