株式会社極東書店トップ > 商品一覧 > Modelling Spatial Density : Data, Methods, and R Applications in Statistics, Econometrics, and Machine Learning.
商品詳細
Modelling Spatial Density : Data, Methods, and R Applications in Statistics, Econometrics, and Machine Learning.
・ISBN 978-0-19-897518-2 paper GB£ 45.00
¥14,256.- (税込) ※(※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
お気に入り
★★★
| 著者・編者 | Kopczewska, Katarzyna, |
|---|---|
| 出版社 | (Oxford University Press, UK) |
| 出版年月 | 2025 |
| ページ数 | 320 pp. |
| 言語 | ENG |
| ニュース番号 | <M25-15139> |
解説
In an era where geo-located point data has become the backbone of socio-economic, environmental, and urban research, understanding spatial density is crucial. Yet the tools for analysing this data have remained scattered and incomplete. Modelling Spatial Density fills a significant gap by providing a comprehensive, practical, and user-friendly guide to modelling spatial density using cutting-edge quantitative methods. Bridging the worlds of spatial statistics, spatial econometrics, and spatial machine learning, Kopczewska introduces a range of established and novel techniques, made accessible through intuitive explanations, open data, and reproducible R code. Lesser and well-known methods are elegantly combined and discussed in non-mathematical language that is accessible to social scientists. The book makes a significant contribution to the synthesis, development, and application of spatial quantitative methods for spatial density in the social and environmental sciences. Writing for researchers, policymakers, and analysts, the author demystifies complex methods, making them accessible to non-mathematicians while maintaining the rigour expected by specialists. With a focus on practical applications, empirical examples, and actionable insights, this resource empowers readers to turn data into evidence for decision-making. Whether you are exploring urban dynamics, environmental challenges, or socio-economic phenomena, this book provides the essential tools for spatial analysis, bringing clarity and precision to your research.