Spatial Outlier Accommodation Using a Spatial Variance Shift Outlier Model

Outlier detection has been a long-debated subject among researchers due to its effect on model fitting. Spatial outlier received considerable attention in the recent past. On other hand, accommodation, particularly spatial applications, retains vital information about model. It is pertinent develop method that capable of accommodating detected outliers fashion models. In this paper, we formulate variance shift (SVSOM) regression as robust using restricted maximum likelihood (REML) and use weights based The are accommodated via revised for observations with help SVSOM. Simulation results show SVSOM, more efficient than general (GSM). findings study also reveal contamination residuals x variable have little parameter estimates y always detectable. Asymptotic distribution squared prediction obtained confirm outlyingness an observation. merit or proposed SVSOM confirmed artificial COVID-19 data sets.