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:: Volume 18, Issue 2 (2-2025) ::
JSS 2025, 18(2): 0-0 Back to browse issues page
Autoregressive Spatial Regression Model and Second-Order Moving Average for Generalized Skew-Laplace Random Field
Mohammad Mehdi Saber * , Mohsen Mohammadzadeh
Abstract:   (661 Views)
In this article, autoregressive spatial regression and second-order moving average will be presented to model the outputs of a heavy-tailed skewed spatial random field resulting from the developed multivariate generalized Skew-Laplace distribution. The model parameters are estimated by the maximum likelihood method using the Kolbeck-Leibler divergence criterion. Also, the best spatial predictor will be provided. Then, a simulation study is conducted to validate and evaluate the performance of the proposed model. The method is applied to analyze a real data.
Keywords: Multivariate generalized skew Laplace distribution, Autoregressive and moving average spatial regression model, Kolbeck-Leibler divergence.
Full-Text [PDF 401 kb]   (399 Downloads)    
Type of Study: Research | Subject: Spatial Statistics
Received: 2024/05/17 | Accepted: 2024/05/30 | Published: 2024/12/2
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Saber M M, Mohammadzadeh M. Autoregressive Spatial Regression Model and Second-Order Moving Average for Generalized Skew-Laplace Random Field. JSS 2025; 18 (2)
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 18, Issue 2 (2-2025) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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