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Model Building for Random Fields

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Advances in Intelligent Data Analysis (IDA 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2189))

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Abstract

Random fields are used to model spatial data in many application areas. Typical examples are image analysis and agricultural field trials. We focus on the relatively neglected area of model building1 and draw together its widely dispersed literature, which reflects the aspirations of a wide range of application areas. We include a spatial analogue of predictive least squares which may be of independent interest.

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Author information

Authors and Affiliations

  1. Defence Evaluation and Research Agency, Gt. Malvern, WR14 3PS, UK

    R.H. Glendinning

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  1. R.H. Glendinning
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Editors and Affiliations

  1. Royal Institute of Technology, Centre for Autonomous Systems, 10044, Stockholm, Sweden

    Frank Hoffmann

  2. Imperial College, Huxley Building 180 Queen’s Gate, London, SW7 2BZ, UK

    David J. Hand  & Niall Adams  & 

  3. Department of Computer Science, Vanderbilt University, Box 1679, Station B, Nashville, TN, 37235, USA

    Douglas Fisher

  4. Department of Computer Science, New University of Lisbon, 2825-114, Caparica, Portugal

    Gabriela Guimaraes

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Glendinning, R. (2001). Model Building for Random Fields. In: Hoffmann, F., Hand, D.J., Adams, N., Fisher, D., Guimaraes, G. (eds) Advances in Intelligent Data Analysis. IDA 2001. Lecture Notes in Computer Science, vol 2189. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44816-0_30

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  • DOI: https://doi.org/10.1007/3-540-44816-0_30

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42581-6

  • Online ISBN: 978-3-540-44816-7

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