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The spatial distribution of real estate in specific geographic locations, real estate transactions, and the prices and values of properties are a highly complex spatial phenomena that should be analyzed with the use of multidimensional methods. Spatial factors are taken into account in the modeling process to increase the reliability of real estate market analyses, and spatial autoregressive models are applied to determine the effect of spatial factors on real estate prices and values. The present study relies on a review of the literature and the results of an experiment. The concept and principles of market analysis were designed with the use of spatial autoregressive models, and the influence of selected spatial factors on real estate prices was presented on maps. Analyses involving autoregressive models enable reliable modeling and support correct interpretation of the observed processes.

The Application of Spatial Autoregressive Models for Analyzing the Influence of Spatial Factors on Real Estate Prices and Values