Multi angle

H 1 Fourier based methods for spatial data observed on irregularly spaced locations

Auteurs : Subba Rao, Suhasini (Auteur de la Conférence)
CIRM (Editeur )

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    Résumé : In this talk we introduce a class of statistics for spatial data that is observed on an irregular set of locations. Our aim is to obtain a unified framework for inference and the statistics we consider include both parametric and nonparametric estimators of the spatial covariance function, Whittle likelihood estimation, goodness of fit tests and a test for second order spatial stationarity. To ensure that the statistics are computationally feasible they are defined within the Fourier domain, and in most cases can be expressed as a quadratic form of a discrete Fourier-type transform of the spatial data. Evaluation of such statistic is computationally tractable, requiring $O(nb)$ operations, where $b$ are the number Fourier frequencies used in the definition of the statistic (which varies according to the application) and $n$ is the sample size. The asymptotic sampling properties of the statistics are derived using mixed spatial asymptotics, where the number of locations grows at a faster rate than the size of the spatial domain and under the assumption that the spatial random field is stationary and the irregular design of the locations are independent, identically distributed random variables. We show that there are quite intriguing differences in the behaviour of the statistic when the spatial process is Gaussian and non-Gaussian. In particular, the choice of the number of frequencies $b$ in the construction of the statistic depends on whether the spatial process is Gaussian or not. If time permits we describe how the results can also be used in variance estimation. And if we still have time some simulations and real data will be presented.

    Codes MSC :
    62F12 - Asymptotic properties of estimators
    62G05 - Nonparametric estimation
    62M10 - Time series, auto-correlation, regression, etc.
    62M30 - Statistics of spatial processes

      Informations sur la Vidéo

      Langue : Anglais
      Date de publication : 01/03/16
      Date de captation : 16/02/16
      Collection : Probability and Statistics
      Sous collection : Research talks
      Format : MP4
      Domaine : Probability & Statistics
      Durée : 00:39:36
      Audience : Chercheurs ; Doctorants , Post - Doctorants
      Download : https://videos.cirm-math.fr/2016-02-16_Subba_Rao.mp4

    Informations sur la rencontre

    Nom de la rencontre : Thematic month on statistics - Week 3: Processus / Mois thématique sur les statistiques - Semaine 3 : Processus
    Organisateurs de la rencontre : Boutahar, Mohamed ; Reboul, Laurence
    Dates : 15/02/16 - 19/02/16
    Année de la rencontre : 2016
    URL Congrès : http://conferences.cirm-math.fr/1617.html

    Citation Data

    DOI : 10.24350/CIRM.V.18932403
    Cite this video as: Subba Rao, Suhasini (2016). Fourier based methods for spatial data observed on irregularly spaced locations. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.18932403
    URI : http://dx.doi.org/10.24350/CIRM.V.18932403

    Voir aussi


    1. Suhasini Subba Rao. (2014). Fourier based statistics for irregular spaced spatial data. - http://arxiv.org/abs/1405.5240

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