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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.

ASIN ‏ : ‎ B08K3PWTTQ
Publisher ‏ : ‎ Routledge; 1st edition (November 25, 2020)
Publication date ‏ : ‎ November 25, 2020
Language ‏ : ‎ English
File size ‏ : ‎ 382.7 MB
Simultaneous device usage ‏ : ‎ Up to 4 simultaneous devices, per publisher limits
Text-to-Speech ‏ : ‎ Not enabled
Enhanced typesetting ‏ : ‎ Not Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 620 pages
Format ‏ : ‎ Print Replica