Applied Spatial Data Analysis with R

Author:   Roger S. Bivand ,  Edzer J. Pebesma ,  Virgilio Gomez-Rubio
Publisher:   Springer-Verlag New York Inc.
Edition:   2008 ed.
ISBN:  

9780387781709


Pages:   390
Publication Date:   01 July 2008
Format:   Paperback
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Applied Spatial Data Analysis with R


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Overview

This book addresses the needs of researchers and students using R to analyze spatial data across a range of disciplines and professions. The book is co-authored by a group involved in the Comprehensive R Archive Network.

Full Product Details

Author:   Roger S. Bivand ,  Edzer J. Pebesma ,  Virgilio Gomez-Rubio
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2008 ed.
Dimensions:   Width: 15.60cm , Height: 2.00cm , Length: 23.40cm
Weight:   0.548kg
ISBN:  

9780387781709


ISBN 10:   0387781706
Pages:   390
Publication Date:   01 July 2008
Audience:   Professional and scholarly ,  College/higher education ,  Professional & Vocational ,  Undergraduate
Format:   Paperback
Publisher's Status:   Unknown
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

Reviews

From the reviews: The first half of this book certainly convinced me that some extra effort in organizing my data into certain spatial class structures makes the analysis easier and less subject to mistakes. I also admit that I found it very interesting and I learned a lot. Several years ago, I struggled on a project that required managing various spatial data with different projections and support using the rgdal package in R; I really wish I had this book at that time!... In summary, this is an excellent book that should be on the shelf of any applied statistician who is analyzing spatial data using R.!, [I]t would be a valuable companion to any course that uses spatial packages in R. (Jay M. Ver Hoef, Biometrics, June 2009, 65) Applied Spatial Data Analysis with R is an accessible text that demonstrates and explains the handling of spatial data using the R software platform. The authors have all been key contributors to the R spatial data analysis community, and the range of their contributions is evident from the comprehensive coverage of this work. It will appeal to those familiar with R but not spatial data, and vice versa, as well as those proficient in both and in search of a reference text.! In short, this book is highly recommended to statisticians and geographers interested in plotting and analyzing spatial data. (James Cheshire, Significance September 2009) I would highly recommend instructors, students, and researchers to have this text on their bookshelf. This book is an enrichment for the community of people conducting research in spatial statistics. It provides tools for simple spatial problems as well as for cutting edge research problems. The book is priced reasonably relative to its content. Overall, it is an excellent reference book. (The American Statistician, May 2010, Vol. 64, No. 2)


"From the reviews: ""The first half of this book certainly convinced me that some extra effort in organizing my data into certain spatial class structures makes the analysis easier and less subject to mistakes. I also admit that I found it very interesting and I learned a lot. Several years ago, I struggled on a project that required managing various spatial data with different projections and support using the rgdal package in R; I really wish I had this book at that time!... In summary, this is an excellent book that should be on the shelf of any applied statistician who is analyzing spatial data using R..., [I]t would be a valuable companion to any course that uses spatial packages in R."" (Jay M. Ver Hoef, Biometrics, June 2009, 65) ""Applied Spatial Data Analysis with R is an accessible text that demonstrates and explains the handling of spatial data using the R software platform. The authors have all been key contributors to the R spatial data analysis community, and the range of their contributions is evident from the comprehensive coverage of this work. It will appeal to those familiar with R but not spatial data, and vice versa, as well as those proficient in both and in search of a reference text... In short, this book is highly recommended to statisticians and geographers interested in plotting and analyzing spatial data."" (James Cheshire, Significance September 2009) ""I would highly recommend instructors, students, and researchers to have this text on their bookshelf. This book is an enrichment for the community of people conducting research in spatial statistics. It provides tools for simple spatial problems as well as for cutting edge research problems. The book is priced reasonably relative to its content. Overall, it is an excellent reference book."" (The American Statistician, May 2010, Vol. 64, No. 2) ""This book constitutes a complete and accessible manual dedicated to the use of R for handling spatial data. ... the book will appeal equally to beginners and to experts in the field of spatial data analysis. ... As a summary, I strongly recommend this book to any person who needs to study the behaviour of one or several geo-referenced variables. ... It certainly gives a good and quite exhaustive overview to the different techniques available in order to characterize spatial data."" (Didier Renard, Mathematical Geosciences, Vol. 43, 2011)"


From the reviews: The first half of this book certainly convinced me that some extra effort in organizing my data into certain spatial class structures makes the analysis easier and less subject to mistakes. I also admit that I found it very interesting and I learned a lot. Several years ago, I struggled on a project that required managing various spatial data with different projections and support using the rgdal package in R; I really wish I had this book at that time!... In summary, this is an excellent book that should be on the shelf of any applied statistician who is analyzing spatial data using R.!, [I]t would be a valuable companion to any course that uses spatial packages in R. (Jay M. Ver Hoef, Biometrics, June 2009, 65) Applied Spatial Data Analysis with R is an accessible text that demonstrates and explains the handling of spatial data using the R software platform. The authors have all been key contributors to the R spatial data analysis community, and the range of their contributions is evident from the comprehensive coverage of this work. It will appeal to those familiar with R but not spatial data, and vice versa, as well as those proficient in both and in search of a reference text.! In short, this book is highly recommended to statisticians and geographers interested in plotting and analyzing spatial data. (James Cheshire, Significance September 2009) I would highly recommend instructors, students, and researchers to have this text on their bookshelf. This book is an enrichment for the community of people conducting research in spatial statistics. It provides tools for simple spatial problems as well as for cutting edge research problems. The book is priced reasonably relative to its content. Overall, it is an excellent reference book. (The American Statistician, May 2010, Vol. 64, No. 2) This book constitutes a complete and accessible manual dedicated to the use of R for handling spatial data. ! the book will appeal equally to beginners and to experts in the field of spatial data analysis. ! As a summary, I strongly recommend this book to any person who needs to study the behaviour of one or several geo-referenced variables. ! It certainly gives a good and quite exhaustive overview to the different techniques available in order to characterize spatial data. (Didier Renard, Mathematical Geosciences, Vol. 43, 2011)


From the reviews: The first half of this book certainly convinced me that some extra effort in organizing my data into certain spatial class structures makes the analysis easier and less subject to mistakes. I also admit that I found it very interesting and I learned a lot. Several years ago, I struggled on a project that required managing various spatial data with different projections and support using the rgdal package in R; I really wish I had this book at that time!... In summary, this is an excellent book that should be on the shelf of any applied statistician who is analyzing spatial data using R..., [I]t would be a valuable companion to any course that uses spatial packages in R. (Jay M. Ver Hoef, Biometrics, June 2009, 65) Applied Spatial Data Analysis with R is an accessible text that demonstrates and explains the handling of spatial data using the R software platform. The authors have all been key contributors to the R spatial data analysis community, and the range of their contributions is evident from the comprehensive coverage of this work. It will appeal to those familiar with R but not spatial data, and vice versa, as well as those proficient in both and in search of a reference text... In short, this book is highly recommended to statisticians and geographers interested in plotting and analyzing spatial data. (James Cheshire, Significance September 2009) I would highly recommend instructors, students, and researchers to have this text on their bookshelf. This book is an enrichment for the community of people conducting research in spatial statistics. It provides tools for simple spatial problems as well as for cutting edge research problems. The book is priced reasonably relative to its content. Overall, it is an excellent reference book. (The American Statistician, May 2010, Vol. 64, No. 2) This book constitutes a complete and accessible manual dedicated to the use of R for handling spatial data. ... the book will appeal equally to beginners and to experts in the field of spatial data analysis. ... As a summary, I strongly recommend this book to any person who needs to study the behaviour of one or several geo-referenced variables. ... It certainly gives a good and quite exhaustive overview to the different techniques available in order to characterize spatial data. (Didier Renard, Mathematical Geosciences, Vol. 43, 2011)


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