Bayesian spatial regression models with closed skew normal correlated errors and missing observations |
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Authors: | Omid Karimi Mohsen Mohammadzadeh |
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Institution: | 1. Department of Statistics, Tarbiat Modares University, Tehran, Iran
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Abstract: | This paper is concerned with Bayesian estimation of a spatial regression model with skew non-Gaussian errors. The regression
parameters are estimated by using a closed skew normal (CSN) distribution, which is closed under conditioning and linear combination.
The proposed model captures skewness in the response variable. Sometimes, we may encounter missing observations in the response
variable, accordingly we model and predict the missing observations by a Bayesian approach using Gibbs sampling methods. Next,
a simulation study is performed to asses our model validity. Also, the proposed model in this work is applied to CO data from
Tehran, the capital city of Iran. Then, the accuracy of the CSN and Gaussian models is compared by cross validation criterion. |
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Keywords: | |
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