• DocumentCode
    1116486
  • Title

    Planar-Temporal Stationary Correlation Models That Depend on the Maximum Norm

  • Author

    Ma, Chunsheng

  • Author_Institution
    Dept. of Math. & Stat., Wichita State Univ., KS
  • Volume
    55
  • Issue
    3
  • fYear
    2007
  • fDate
    3/1/2007 12:00:00 AM
  • Firstpage
    889
  • Lastpage
    896
  • Abstract
    It is useful to have various stochastic models to describe a wide range of spatial or spatio-temporal dependence and interaction. Two families of planar-temporal stationary correlation functions are proposed in this paper, whose planar margins are functions of the maximum norm on the plane. We formulate each of these two families through a simple development base that possesses a rational spectral density. The base for one family is the linear combination of two separable planar-temporal correlation models, while there seems to be no easy interpretation for the base of the other family. Each family is then generated by appropriately randomizing the planar and temporal coordinates of the base random field. One may treat each family as a semiparametric model, whose permissible parameter domains are identified. A common feature of the models developed is that they allow for describing positive and negative correlations. Other properties are also presented
  • Keywords
    correlation theory; planar-temporal stationary correlation models; rational spectral density; semiparametric model; spatio-temporal dependence; Biological system modeling; Biological systems; Biomedical signal processing; Fourier transforms; Geophysical measurements; Geophysical signal processing; Particle measurements; Power system modeling; Predictive models; Stochastic processes; Correlation function; Fourier transform; covariance; isotropic; power-law decay; spectral density; stationary;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2006.888062
  • Filename
    4099546