Applied Spatial Statistics Econometrics (49 results)

Gr.-8°, ill. OPp. Condition: Gut. 275 S. Gut; Rücken geblichen, sonst sehr gut - textsauber 04-60680 9789024736270 + + + Versand noch am gleichen Tag bei Bestelleingang werktags bis 15 Uhr + + + Alle Preise inkl. MWSt. + + + Sprache: Englisch Gewicht in Gramm: 680.

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Condition: New. 2020. 1st Edition. Paperback. . . . . .

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Paperback. Condition: New. 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.…

Condition: New. Katarzyna Kopczewska is Professor of Economics at the Faculty of Economic Sciences, University of Warsaw, and Head of the Spatial Warsaw research group. She specialises in methodology of spatial analytics for geolocalised socio-economic processes.

Condition: New. 2020. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Condition: New. 2026. 2nd Edition. paperback. . . . . . Books ship from the US and Ireland.

Taschenbuch. Condition: Neu. Neuware - Now in its second edition, Applied Spatial Statistics and Econometrics offers a modern and accessible introduction to spatial data analysis using R. Emphasising reproducibility, real-world datasets, and practical workflows, this comprehensive guide introduces spatial thinking from a critical analytical perspective, highlighting the importance of location, distance, and neighbourhood effects in shaping social and economic phenomena.Readers are guided through foundational concepts, including spatial data structures (areal, point, and grid data), visualisation techniques, and spatial econometric models such as spatial lag, spatial error, and spatial Durbin specifications. Updates reflect the substantial evolution of spatial models and R packages, such as the transition to sf:: and terra:: packages, enhancements to spatstat:: package, new tools for spatial sampling and bootstrap, and fully reproducible analyses with complete R code. Topics include geographically weighted regression, spatial point pattern analysis, DEGURBA classification, and spatial principal component analysis.Accompanied by datasets and complete R code on GitHub and RPubs, the book enables readers to replicate analyses and adapt methods to their own research. It is an essential resource for advanced students of econometrics, spatial planning, and regional science, as well as researchers and data scientists seeking to harness the power of spatial analysis for evidence-based insights and policy recommendations.…

Paperback. Condition: Brand New. 520 pages. 11.25x8.50x1.25 inches. In Stock.

hardcover. Condition: Sehr gut. 288 Seiten; 9789024736270.2 Gewicht in Gramm: 1.

Hardcover. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Paperback. Condition: New. 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.…

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