03695nam a22005415i 4500 978-981-97-4022-2 DE-He213 20251030112837.0 cr nn 008mamaa 240803s2024 si | s |||| 0|eng d 9789819740222 978-981-97-4022-2 10.1007/978-981-97-4022-2 doi G70.212-.217 RGW bicssc SCI030000 bisacsh RGW thema He, Xindong. author. (orcid)0000-0003-0749-0500 https://orcid.org/0000-0003-0749-0500 aut http://id.loc.gov/vocabulary/relators/aut 81906 Geographic Data Analysis Using R [electronic resource] / by Xindong He. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XX, 225 p. 100 illus., 78 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Introduction to Geographic Data and R -- Descriptive Analysis of Geographic Data -- Correlation Analysis -- Linear Regression Analysis -- Geographically Weighted Regression Analysis -- Time Series Analysis -- Cluster Analysis -- Principal Component Analysis (PCA) -- Markov Chain Analysis -- Geographic Network Analysis -- Spatial Interpolation. This book is structured to encompass both the foundational and specialized aspects of quantitative analysis in geography. The basic content covers descriptive statistical analysis and correlation analysis of geographical data, while the professional content delves into more advanced topics like linear regression analysis, geographically weighted regression analysis, time series analysis, cluster analysis, principal component analysis, Markov chain analysis, and geographical network analysis. The methodologies span from widely utilized techniques to more recent developments, and the data primarily originates from reputable sources in China. The example code provided in the book can be executed using R packages available on the CRAN website. This book is an invaluable resource for undergraduate and graduate students, as well as researchers interested in learning and applying R for processing, visualizing, and analyzing geographic data. It serves as an introductory course in quantitative methods in geography for students in geography departments. Additionally, it is an ideal supplementary text for applied methods courses across various disciplines that involve geographic data, such as human and physical geography, geographic information science, ecology, public health, crime, and economics. . Geographic information systems. 61967 Regression analysis. 61412 Environmental geography. 69017 Operations research. 57943 Geographical Information System. 66422 Linear Models and Regression. 76680 Integrated Geography. 69018 Operations Research and Decision Theory. 67143 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819740215 Printed edition: 9789819740239 Printed edition: 9789819740246 https://doi.org/10.1007/978-981-97-4022-2 ZDB-2-EES ZDB-2-SXEE 62237 62237