Transformation-based generalized spatial regression using the spmoran package: Case study examples

TL;DR

This paper demonstrates the application of the spmoran package for generalized spatial regression modeling of count and non-Gaussian data, showcasing disease mapping, spatial prediction, and hedonic analysis with practical R code examples.

Contribution

It introduces the spmoran package for generalized spatial regression and provides case studies illustrating its use for various spatial data analyses.

Findings

Successful modeling of count and non-Gaussian data using spmoran

Application examples include disease mapping and spatial prediction

Availability of R code for reproducibility

Abstract

This study presents application examples of generalized spatial regression modeling for count data and continuous non-Gaussian data using the spmoran package (version 0.2.2 onward). Section 2 introduces the model. The subsequent sections demonstrate applications of the model for disease mapping, spatial prediction and uncertainty modeling, and hedonic analysis. The R codes used in this vignette are available from https://github.com/dmuraka/spmoran. Another vignette focusing on Gaussian spatial regression modeling is also available from the same GitHub page.