Bidimensional Regression in Spatial Analysis
Bidimensional Regression in Spatial Analysis

Summary/Abstract: Bidimensional regression is a method developed by Waldo Tobler for comparing the degree of resemblance between two two-dimensional configurations of points or surfaces. It is an extension of linear regression where each variable is a pair of values representing a location in a two-dimensional space. Bidimensional regression numerically compares the similarity between two-dimensional surfaces through an index called bidimensional correlation. The aim of the study is the general description of the method, and to present examples of its application with the help of some real data, that of the Hungarian railway time space.

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