Free PDF Applied Spatial Data Analysis with R (Use R!)
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Applied Spatial Data Analysis with R (Use R!)
Free PDF Applied Spatial Data Analysis with R (Use R!)
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Review
“The book’s tone and technical focus … suits well its intended audience: advanced or intermediate users of R wanting to improve their spatial analysis skills. … this book is the authoritative resource on R’s spatial capabilities. I heartily recommend ASDAR to all existing R users interested in spatial data and adventurous R beginners with a strong grounding in GIS.†(Robin Lovelace, Applied Spatial Analysis and Policy, Vol. 8, 2015)
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From the Back Cover
Applied Spatial Data Analysis with R, Second Edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.
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Product details
Series: Use R! (Book 10)
Paperback: 424 pages
Publisher: Springer; 2nd ed. 2013 edition (June 21, 2013)
Language: English
ISBN-10: 9.78146E+12
ISBN-13: 978-1461476177
ASIN: 1461476178
Product Dimensions:
6.1 x 1 x 9.2 inches
Shipping Weight: 1.6 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
22 customer reviews
Amazon Best Sellers Rank:
#504,415 in Books (See Top 100 in Books)
This is not a book for a beginner, but is an excellent book for two groups of readers: those who have some background with R and wish to learn about its capabilities for spatial statistics; and those with some background in spatial statistics who wish to learn how to use R. The authors have been the main developers of the spatial statistics packages on R, and therefore know the packages intimately. But the authors also have a deep knowledge of the spatial statistics literature, and I found myself learning something new about these methods in every chapter. Everyone serious about spatial statistics should see what R has to offer. This book is the easiest way to do that.
This book fills a gap in the Spatial Statistics literature. Most of the treatises are heavy on the math, and I find it difficult to bridge the gap between the formulas and applying them. The modules for R take care of this for you and leave you to interpret the result. This book covers most of these modules and demonstrates how to use them. Really worth getting. There is also the ESRI Guide to GIS Analysis Vol 2, but it is more of an introductory text.
Difficult to read. Apparently it is available as a free ebook elsewhere! Ended up not really using it for my Geospatial Statistics course, but such is life.
Its a good book but does not provide enough background.
This is a great book that I refer to on a regular basis. There is a sufficient amount of math, so that users have some background on procedures. There is a great collection of examples with R code so that procedures can be easily implemented. Most of the procedures use standard frequentist methods, though there are a few examples of Bayesian analyses. Highly recommended for applied scientists who are comfortable with basic concepts of statistics, R, and GIS.
I was really excited when I ordered this book as it looked like the type of material I had been looking for for ages, but as it turns out I am mildly disappointed in it, primarily because I found the text somewhat hard to grasp and the code not particularly well explained. It is still a very good read though and certainly helped me enhance my knowledge of statistical analyses in R. I would definitely recommend it to anyone looking to examine spatial data in R, but there is a bit of homework to do to be able to understand how all the pieces fit together.
Easier to read than many other statistics books and very informative
I purchased this book for a professor in our department. I had purchased another book from GoodWell of Silicon Valley from another professor. Both professors were impressed with the quality of the used book and the price. The price was also a great find into todays market.
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