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Bayesian spatial regression models with closed skew normal correlated errors and missing observations

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  • Omid Karimi
  • Mohsen Mohammadzadeh

Abstract

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  • Omid Karimi & Mohsen Mohammadzadeh, 2012. "Bayesian spatial regression models with closed skew normal correlated errors and missing observations," Statistical Papers, Springer, vol. 53(1), pages 205-218, February.
    • Handle: RePEc:spr:stpapr:v:53:y:2012:i:1:p:205-218
    DOI: 10.1007/s00362-010-0329-2
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    References listed on IDEAS

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    1. Oh, Man-Suk & Shin, Dong Wan & Kim, Han Joon, 2002. "Bayesian analysis of regression models with spatially correlated errors and missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 387-400, June.
    2. Susanne Gschlößl & Claudia Czado, 2008. "Modelling count data with overdispersion and spatial effects," Statistical Papers, Springer, vol. 49(3), pages 531-552, July.
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    Cited by:

    1. Reinaldo B. Arellano-Valle & Adelchi Azzalini, 2022. "Some properties of the unified skew-normal distribution," Statistical Papers, Springer, vol. 63(2), pages 461-487, April.
    2. Adriano Zanin Zambom & Gregory J. Matthews, 2021. "Sure independence screening in the presence of missing data," Statistical Papers, Springer, vol. 62(2), pages 817-845, April.
    3. Levon Demirdjian & Majid Mojirsheibani, 2019. "Kernel classification with missing data and the choice of smoothing parameters," Statistical Papers, Springer, vol. 60(5), pages 1487-1513, October.
    4. Majid Mojirsheibani & Timothy Reese, 2017. "Kernel regression estimation for incomplete data with applications," Statistical Papers, Springer, vol. 58(1), pages 185-209, March.
    5. Rezaie, Javad & Eidsvik, Jo, 2014. "Kalman filter variants in the closed skew normal setting," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 1-14.
    6. Yu Shen & Han-Ying Liang, 2018. "Quantile regression and its empirical likelihood with missing response at random," Statistical Papers, Springer, vol. 59(2), pages 685-707, June.

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