On the Four Types of Weight Functions for Spatial Contiguity Matrix

TL;DR

This paper analyzes four common weight functions for spatial autocorrelation models using ACF and PACF, aiming to guide the selection of appropriate functions based on their autocorrelation characteristics.

Contribution

It introduces a method to compare and select spatial weight functions by analyzing their autocorrelation functions, enhancing spatial analysis accuracy.

Findings

Different weight functions have distinct autocorrelation profiles.

Guidelines for choosing weight functions based on ACF and PACF characteristics.

Improved understanding of spatial contiguity matrix construction.

Abstract

This is a "spatial autocorrelation analysis" of spatial autocorrelation. I use the 1-dimension spatial autocorrelation function (ACF) and partial autocorrelation function (PACF) to analyze four kinds of weight function in common use for the 2-dimensional spatial autocorrelation model. The aim of this study is at how to select a proper weight function to construct a spatial contiguity matrix for spatial analysis. The scopes of application of different weight functions are defined in terms of the characters of their ACFs and PACFs.