Applied spatial statistics and econometrics data analysis in R
"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 showcase key topics including unsupervised learning, cau...
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Format: | UnknownFormat |
Sprache: | eng |
Veröffentlicht: |
London, New York
Routledge, Taylor & Francis Group
2021
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Schriftenreihe: | Routledge advanced texts in economics and finance
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Schlagworte: | |
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Zusammenfassung: | "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 showcase 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"-- |
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Beschreibung: | Includes bibliographical references and index |
Beschreibung: | xxv, 593 Seiten Illustrationen, Diagramme, Karten |
ISBN: | 9780367470777 978-0-367-47077-7 9780367470760 978-0-367-47076-0 |