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Space-time correlation analysis: a comparative study

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  • Sandra De Iaco

Abstract

Space-time correlation modelling is one of the crucial steps of traditional structural analysis, since space-time models are used for prediction purposes. A comparative study among some classes of space-time covariance functions is proposed. The relevance of choosing a suitable model by taking into account the characteristic behaviour of the models is proved by using a space-time data set of ozone daily averages and the flexibility of the product-sum model is also highlighted through simulated data sets.

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  • Sandra De Iaco, 2010. "Space-time correlation analysis: a comparative study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 1027-1041.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:6:p:1027-1041
    DOI: 10.1080/02664760903019422
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    References listed on IDEAS

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    1. De Iaco, S. & Myers, D. E. & Posa, D., 2002. "Space-time variograms and a functional form for total air pollution measurements," Computational Statistics & Data Analysis, Elsevier, vol. 41(2), pages 311-328, December.
    2. Cesare, L. De & Myers, D. E. & Posa, D., 2001. "Estimating and modeling space-time correlation structures," Statistics & Probability Letters, Elsevier, vol. 51(1), pages 9-14, January.
    3. Iaco, S. De & Myers, D. E. & Posa, D., 2001. "Space-time analysis using a general product-sum model," Statistics & Probability Letters, Elsevier, vol. 52(1), pages 21-28, March.
    4. Ma, Chunsheng, 2003. "Spatio-temporal stationary covariance models," Journal of Multivariate Analysis, Elsevier, vol. 86(1), pages 97-107, July.
    5. De Iaco, S. & Palma, M. & Posa, D., 2005. "Modeling and prediction of multivariate space-time random fields," Computational Statistics & Data Analysis, Elsevier, vol. 48(3), pages 525-547, March.
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