This article introduces a random field defined by the generalized t-squared multivariate distributionØ which allows for improved accuracy in spatial prediction. With its flexibility for heavy-tailed and light-tailed dataØ this random field is suitable for predicting both types of spatial data. The simulation results demonstrate that incorporating this random field enhances prediction accuracy.Ø particularly in scenarios with limited spatial data.
Mathematical Research