Extended Generalized Skew Laplace Random Field: Spatial Autoregressive and Moving Average Model for Prediction of Missing Data in Skew and Heavy Tailed Data | ||
| Journal of Sciences, Islamic Republic of Iran | ||
| مقاله 7، دوره 32، شماره 2، تابستان 2021، صفحه 169-178 اصل مقاله (1.54 M) | ||
| نوع مقاله: Original Research Articles | ||
| شناسه دیجیتال (DOI): 10.22059/jsciences.2021.315726.1007606 | ||
| نویسندگان | ||
| Mohammad Mehdi Saber* 1؛ Alireza Nematollahi2؛ Mohsen Mohammadzadeh3 | ||
| 11 Department of Statistics, Higher Education Center of Eghlid, Eghlid, Islamic Republic of Iran | ||
| 22 Department of Statistics, Faculty of Sciences, Shiraz University, Shiraz, Islamic Republic of Iran | ||
| 33 Department of Statistics, Faculty of Sciences, Tarbiat Modares University, Tehran, Islamic Republic of Iran | ||
| چکیده | ||
| In this paper, we define a spatial skew and heavy-tailed random field by an extended version of multivariate generalized skew Laplace distribution. The Bayesian spatial regression model is developed to explain the spatial data. A simulation study is then carried out to validate and evaluate the performance of the proposed model. The application of this model is also demonstrated in an analysis of a geological real data set. | ||
| کلیدواژهها | ||
| Multivariate generalized skew Laplace distribution؛ SARMA model؛ MCMC algorithm | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 646 تعداد دریافت فایل اصل مقاله: 552 |
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