:: Volume 15, Issue 2 (3-2022) ::
JSS 2022, 15(2): 567-590 Back to browse issues page
Introduce a Survival Model with Spatial Skew Gaussian Random Effects and its Application in Covid-19 Data Analysis
Kiomars Motarjem *
Abstract:   (2238 Views)

The prevalence of Covid-19 is greatly affected by the location of the patients. From the beginning of the pandemic, many models have been used to analyze the survival time of  Covid-19 patients. These models often use the Gaussian random field to include this effect in the survival model. But the assumption of Gaussian random effects is not realistic. In this paper, by considering a spatial skew Gaussian random field for random effects and a new spatial survival model is introduced. Then, in a simulation study, the performance of the proposed model is evaluated.  Finally, the application of the model to analyze the survival time data of Covid-19 patients in Tehran is presented.

Keywords: Spatial Survival Data, Spatial Survival Model, Skew Gaussian Random Field, Covid-19.
Full-Text [PDF 314 kb]   (1277 Downloads)    
Type of Study: Research | Subject: Spatial Statistics
Received: 2021/03/13 | Accepted: 2022/03/1 | Published: 2021/10/4



XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 15, Issue 2 (3-2022) Back to browse issues page