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Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Katarzyna Kopczewska is Professor of Economics at the Faculty of Economic Sciences, University of Warsaw, and Head of the Spatial Warsaw research group. She specializes in methodology of spatial analytics for geolocalised socio-economic processes.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Applied Spatial Statistics and Econometrics (Paperback)
Edité par
Taylor & Francis Ltd, London, 2026
ISBN 10 : 1041002661
ISBN 13 : 9781041002666
Neuf
Paperback
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. 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. Now in its second edition, Applied Spatial Statistics and Econometrics offers a modern and accessible introduction to spatial data analysis using R. It introduces spatial thinking from an analytical perspective, highlighting importance of location, distance, and neighbourhood effects in shaping social and economic phenomena. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781041002666
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Applied Spatial Statistics and Econometrics
Edité par
Taylor & Francis, 2026
ISBN 10 : 1041002661
ISBN 13 : 9781041002666
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : 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. N° de réf. du vendeur 3000107856
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Applied Spatial Statistics and Econometrics (Paperback)
Edité par
Taylor & Francis Ltd, London, 2026
ISBN 10 : 1041002661
ISBN 13 : 9781041002666
Neuf
Paperback
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. 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. Now in its second edition, Applied Spatial Statistics and Econometrics offers a modern and accessible introduction to spatial data analysis using R. It introduces spatial thinking from an analytical perspective, highlighting importance of location, distance, and neighbourhood effects in shaping social and economic phenomena. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781041002666
Acheter neuf
EUR 110,05
Expédition à EUR 44,18
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Applied Spatial Statistics and Econometrics : Data Analysis in R
Edité par
Taylor & Francis Ltd Nov 2026, 2026
ISBN 10 : 1041002661
ISBN 13 : 9781041002666
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9781041002666
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Expédition depuis Allemagne vers Etats-Unis
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