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What is R

Chapter 9

Emerging Trends, Techniques, and Applications in Geospatial Data Science

Free programming language for statistical computing and graphics in order to clean, analyze and graph data. It is has many advantages over alternatives including platform independency, many available packages available and compatibility with machine learning.

Published in Chapter:

Analysis of Real Estate Prices Using Geospatial Data: Models and Tools

Orçun Moralı (Bogazici University, Turkey) and Neslihan Yilmaz (Bogazici University, Turkey)

Source Title: Emerging Trends, Techniques, and Applications in Geospatial Data Science

DOI: 10.4018/978-1-6684-7319-1.ch009

Abstract

The effect of space on real estate prices is critical due to the inherent nature of real estate properties. There exist numerous methodologies in order to incorporate the effect of space into the analysis including the addition of district variables or the use spatial econometric models. Spatial models help with the identification and inference problems compared to the simple hedonic models, yet are harder to work with due to their complexity and resource requirements. In this study, using geospatial data, the authors explain the spatial econometric models and tools available for the analysis of cross sectional real estate data.