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Random Fields

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Part of the book series: Springer Series in Statistics ((SSS))

Abstract

We consider material on random fields because some of the questions posed are natural in the context of random fields. Our discussion will generally follow that of Georgii 1988. The parameter set of the random variables x1 iS is a countable infinite set. A typical case would be that in which S is the set of k-dimensional lattice points. The random variables x i take values in a measure space (E, ε) with ε a σ7-field of subsets of E. E could be countable or a continuous state space like Rd with ε the σ-fieid of Borel subsets of Rd with d a positive integer. The random variables (x i ) ∈s are defined on a probability space (ΩF, µ).

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© 2000 Springer Science+Business Media New York

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Rosenblatt, M. (2000). Random Fields. In: Gaussian and Non-Gaussian Linear Time Series and Random Fields. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1262-1_7

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  • DOI: https://doi.org/10.1007/978-1-4612-1262-1_7

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7067-6

  • Online ISBN: 978-1-4612-1262-1

  • eBook Packages: Springer Book Archive

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