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Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated.  We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, some simulation studies will be explained in the last section.

 

Keywords: Gaussian Process Regression, Logistic Regression, Spatial Analysis

Gaussian Process Regression, Logistic Regression, Spatial Analysis