Applied Spatial Statistics and Econometrics: Data Analysis in R
- ISBN-10
- 1000079783
- ISBN-13
- 9781000079784
- Category
- Business & Economics
- Pages
- 594
- Language
- English
- Published
- 2020-11-26
- Publisher
- Routledge
- Author
- Katarzyna Kopczewska
Description
This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, explaining how to interpret the results and what conclusions can be drawn. The author team showcases key topics, including unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity and bootstrapping. It is accompanied by a suite of data and R code on Github to help readers practise techniques via replication and exercises. This text will be a valuable resource for advanced students of econometrics, spatial planning and regional science. It will also be suitable for researchers and data scientists working with spatial data.
Get the book
Other editions
Similar books
-
Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications
By Arthur Getis, Manfred M. FischerRelevant references are given whenever possible to direct researchers to the most useful writings on the subject. Unlike most compendia of this nature, the book starts out by exploring the available software for spatial analysis.
-
Spatial Econometrics
By Harry Kelejian, Gianfranco PirasThe work particularly focuses on models of uncertainty and estimation under various complications relating to model specifications, data problems, tests of hypotheses, along with systems and panel data extensions which are covered in ...
-
Spatial Econometrics and Spatial Statistics
By A. Getis, J. Lacambra, H. ZollerThis book includes contributions on spatial proximity, spatial patterning and in particular the spatial association (dependence) contained in local map patterns.
-
Advances in Spatial Econometrics: Methodology, Tools and Applications
By Luc Anselin, Raymond Florax, Sergio J. ReyWe also distinguish between urban core-fringe size and urban core-fringe growth effects. This results in two different model specifications, which we will refer to as RU(I) for the growth model, and RU(II) for the size model.
-
Spatial Analysis Using Big Data: Methods and Urban Applications
By Yoshiki Yamagata, Hajime SeyaSpatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems.
-
Applied Spatial Data Analysis with R
By Roger S. Bivand, Edzer Pebesma, Virgilio Gómez-RubioThe notation we use follows mostly that of Christensen (1991), as this text most closely links geostatistics to linear model theory. Good texts on geostatistics are Chil`es and Delfiner (2012), Christensen (1991), Cressie (1993), ...
-
Introduction to Spatial Econometrics
By James LeSage, Robert Kelley PaceLee, L.-F. (2004). “Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Econometric Models,” Econometrica, 72, 1899-1926. Lee, M. and R.K. Pace (2005). “Spatial Distribution of Retail Sales,” Journal of Real ...
-
Morphisms for Quantitative Spatial Analysis
By Daniel A. Griffith, Jean H. P. PaelinckThis book treats the notion of morphisms in spatial analysis, paralleling these concepts in spatial statistics (Part I) and spatial econometrics (Part II).
-
Spatial Econometrics and Spatial Statistics
By A. Getis, J. Lacambra, H. ZollerThis book includes contributions on spatial proximity, spatial patterning and in particular the spatial association (dependence) contained in local map patterns.
-
Advanced Spatial Statistics: Special Topics in the Exploration of Quantitative Spatial Data Series
By Daniel A. GriffithThis work has been undertaken by geographers, statisticians, regional scientists, econometricians, and others (e. g. , sociologists).