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Routledge Applied Spatial Statistics and Econometrics in R

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Description

Master spatial data analysis with this comprehensive textbook from Routledge. Part of the Advanced Texts in Economics and Finance series, this guide provides a practical introduction to using R for complex spatial datasets. Each chapter walks readers through specific methods, offering clear explanations on how to interpret results and draw meaningful conclusions from data. The text covers essential topics such as unsupervised learning, causal inference, spatial weight matrices, spatial econometrics, heterogeneity, and bootstrapping. To support hands-on learning, the book includes access to a suite of data and R code on GitHub. This allows students and researchers to practice techniques through direct replication and exercises, making it a valuable resource for advanced students of econometrics and spatial analysis.

Key Features

Provides a comprehensive introduction to applied spatial data analysis specifically using the R programming language.

Covers advanced technical topics including unsupervised learning, causal inference, and spatial weight matrices.

Includes detailed instruction on spatial econometrics, heterogeneity, and bootstrapping methods.

Comes with a suite of data and R code available on GitHub for practical replication and exercises.

Designed as a resource for advanced students of econometrics and spatial analysis within the Routledge series.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
26 November 2020
Listed Since
12 February 2020

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