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Empirical Bayes Prediction for Space-Time Data Under Separable Model
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Firouzeh Rivaz *   , Mohsen Mohammadzadeh , Majid Jafari Khaledi |
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Abstract: (18431 Views) |
| In Bayesian prediction of a Gaussian space-time model, unknown parameters are considered as random variables with known prior distributions and, then the posterior and Bayesian predictive distributions are approximated with discritization method. Since prior distributions are often unknown, in this paper, parametric priors are considered. Then the empirical Bayes approach is used to estimate the prior distributions. Replacing these estimates in the Bayesian predictive distribution, an empirical Bayes space-time predictor and prediction variance are determined. Then an environmental example is used to illustrate the application of the proposed method. Finally the accuracy of the empirical Bayes space-time predictor is considered with cross validation criterion. |
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| Keywords: Space-Time Data, Prediction, Empirical Bayes Method. |
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Full-Text [PDF 1040 kb]
(3722 Downloads)
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Type of Study: Research |
Subject:
Spatial Statistics
Received: 2011/07/4 | Accepted: 2013/08/13 | Published: 2020/02/18
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