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Information Journal Paper

Title

BAYESIAN SPATIAL PREDICTION FOR A GAUSSIAN RANDOM FIELD WITH NOISY OBSERVATIONS

Pages

  67-76

Abstract

 Spatial prediction of a Gaussian random field in unmeasured sites based on precise observations is easily carried out. But, in practice, because of measurement errors, data contain noise. We assume that noises are independent random variable with distribution (0,t2)and they are also independent of the interest random field. If parameters of the mean, Govariance function and t2 are known, the optimal predictor and its MSE could be determined by usual methods. But, these methods are not desirable when some of the model parameters are random variables. We use the Bayesian approach to determine the optimal predictor and its MSE.

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    APA: Copy

    JAFARI KHALEDI, MAJID, & MOHAMMADZADEH, M.. (2005). BAYESIAN SPATIAL PREDICTION FOR A GAUSSIAN RANDOM FIELD WITH NOISY OBSERVATIONS. RESEARCH JOURNAL OF UNIVERSITY OF ISFAHAN "SCIENCE", 21(1), 67-76. SID. https://sid.ir/paper/55963/en

    Vancouver: Copy

    JAFARI KHALEDI MAJID, MOHAMMADZADEH M.. BAYESIAN SPATIAL PREDICTION FOR A GAUSSIAN RANDOM FIELD WITH NOISY OBSERVATIONS. RESEARCH JOURNAL OF UNIVERSITY OF ISFAHAN "SCIENCE"[Internet]. 2005;21(1):67-76. Available from: https://sid.ir/paper/55963/en

    IEEE: Copy

    MAJID JAFARI KHALEDI, and M. MOHAMMADZADEH, “BAYESIAN SPATIAL PREDICTION FOR A GAUSSIAN RANDOM FIELD WITH NOISY OBSERVATIONS,” RESEARCH JOURNAL OF UNIVERSITY OF ISFAHAN "SCIENCE", vol. 21, no. 1, pp. 67–76, 2005, [Online]. Available: https://sid.ir/paper/55963/en

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