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Spatial data analysis in ecology and...
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Plant, Richard E.
Spatial data analysis in ecology and agriculture using R
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Spatial data analysis in ecology and agriculture using R/ Richard E. Plant.
Author:
Plant, Richard E.
Published:
Boca Raton :CRC Press, : c2012.,
Description:
1 online resource (xv, 637 p.) :ill., maps. :
基督教聖經之智慧書導讀 :
Assuming no prior knowledge of R, Spatial data analysis in ecology and agriculture using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author's spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.
Subject:
Programming Languages. -
Online resource:
http://www.crcnetbase.com/isbn/9781439819142
ISBN:
9781439819142 (electronic bk.)
Spatial data analysis in ecology and agriculture using R
Plant, Richard E.
Spatial data analysis in ecology and agriculture using R
[electronic resource] /Richard E. Plant. - Boca Raton :CRC Press,c2012. - 1 online resource (xv, 637 p.) :ill., maps.
Includes bibliographical references (p. 599-617).
Working with spatial data -- R programming environment -- Statistical properties of spatially autocorrelated data -- Measures of spatial autocorrelation -- Sampling and data collection -- Preparing spatial data for analysis -- Preliminary exploration of spatial data -- Multivariate methods for spatial data exploration -- Spatial data exploration via multiple regression -- Variance estimation, the effective sample size, and the bootstrap -- Measures of bivariate association between two spatial variables -- Mixed model -- Regression models for spatially autocorrelated data -- Bayesian analysis of spatially autocorrelated data -- Analysis of spatiotemporal data -- Analysis of data from controlled experiements -- Assembling conclusions -- Appendix A: Review of mathematical concepts -- Appendix B: The data sets -- Appendix C: An R thesaurus.
Assuming no prior knowledge of R, Spatial data analysis in ecology and agriculture using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author's spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.
ISBN: 9781439819142 (electronic bk.)Subjects--Topical Terms:
382652
Programming Languages.
Index Terms--Genre/Form:
228523
Electronic books.
LC Class. No.: S566.55 / .P53 2012
Dewey Class. No.: 635.0727
National Library of Medicine Call No.: S 566.55
Spatial data analysis in ecology and agriculture using R
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ill., maps.
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Includes bibliographical references (p. 599-617).
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Working with spatial data -- R programming environment -- Statistical properties of spatially autocorrelated data -- Measures of spatial autocorrelation -- Sampling and data collection -- Preparing spatial data for analysis -- Preliminary exploration of spatial data -- Multivariate methods for spatial data exploration -- Spatial data exploration via multiple regression -- Variance estimation, the effective sample size, and the bootstrap -- Measures of bivariate association between two spatial variables -- Mixed model -- Regression models for spatially autocorrelated data -- Bayesian analysis of spatially autocorrelated data -- Analysis of spatiotemporal data -- Analysis of data from controlled experiements -- Assembling conclusions -- Appendix A: Review of mathematical concepts -- Appendix B: The data sets -- Appendix C: An R thesaurus.
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Assuming no prior knowledge of R, Spatial data analysis in ecology and agriculture using R provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology and agriculture. Written in terms of four data sets easily accessible online, this book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Based on the author's spatial data analysis course at the University of California, Davis, the book is intended for classroom use or self-study by graduate students and researchers in ecology, geography, and agricultural science with an interest in the analysis of spatial data.
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http://www.crcnetbase.com/isbn/9781439819142
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