The Resource R for Everyone : Advanced Analytics and Graphics, Jared P. Lander

R for Everyone : Advanced Analytics and Graphics, Jared P. Lander

Label
R for Everyone : Advanced Analytics and Graphics
Title
R for Everyone
Title remainder
Advanced Analytics and Graphics
Statement of responsibility
Jared P. Lander
Creator
Subject
Language
eng
Member of
Cataloging source
DLC
http://library.link/vocab/creatorName
Lander, Jared P
Illustrations
  • illustrations
  • maps
Index
index present
LC call number
QA76.73.R3
LC item number
L36 2014
Literary form
non fiction
Nature of contents
bibliography
NLM call number
QA 276.45 .R3 L36r 2014
Series statement
The Addison Wesley data and analytics series
http://library.link/vocab/subjectName
  • R (Computer program language)
  • Scripting languages (Computer science)
  • Statistics
  • Statistics
  • Computer simulation
  • Computer simulation
  • R (Computer program language)
  • Scripting languages (Computer science)
  • Statistics
  • Statistics
Label
R for Everyone : Advanced Analytics and Graphics, Jared P. Lander
Instantiates
Publication
Bibliography note
Includes bibliographical references and indexes
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Machine generated contents note: 1. Getting R -- 1.1. Downloading R -- 1.2.R Version -- 1.3.32-bit versus 64-bit -- 1.4. Installing -- 1.5. Revolution R Community Edition -- 1.6. Conclusion -- 2. The R Environment -- 2.1.Command Line Interface -- 2.2. RStudio -- 2.3. Revolution Analytics RPE -- 2.4. Conclusion -- 3.R Packages -- 3.1. Installing Packages -- 3.2. Loading Packages -- 3.3. Building a Package -- 3.4. Conclusion -- 4. Basics of R -- 4.1. Basic Math -- 4.2. Variables -- 4.3. Data Types -- 4.4. Vectors -- 4.5. Calling Functions -- 4.6. Function Documentation -- 4.7. Missing Data -- 4.8. Conclusion -- 5. Advanced Data Structures -- 5.1.data.frames -- 5.2. Lists -- 5.3. Matrices -- 5.4. Arrays -- 5.5. Conclusion -- 6. Reading Data into R -- 6.1. Reading CSVs -- 6.2. Excel Data -- 6.3. Reading from Databases -- 6.4. Data from Other Statistical Tools -- 6.5.R Binary Files -- 6.6. Data Included with R -- 6.7. Extract Data from Web Sites -- 6.8. Conclusion--
  • 7. Statistical Graphics -- 7.1. Base Graphics -- 7.2.ggplot2 -- 7.3. Conclusion -- 8. Writing R Functions -- 8.1. Hello, World! -- 8.2. Function Arguments -- 8.3. Return Values -- 8.4.do. call -- 8.5. Conclusion -- 9. Control Statements -- 9.1. If and else -- 9.2.switch -- 9.3.ifelse -- 9.4.Compound Tests -- 9.5. Conclusion -- 10. Loops, the Un-R Way to Iterate -- 10.1. For Loops -- 10.2. While Loops -- 10.3. Controlling Loops -- 10.4. Conclusion -- 11. Group Manipulation -- 11.1. Apply Family -- 11.2.aggregate -- 11.3.plyr -- 11.4.data.table -- 11.5. Conclusion -- 12. Data Reshaping -- 12.1.cbind and rbind -- 12.2. Joins -- 12.3.reshape2 -- 12.4. Conclusion -- 13. Manipulating Strings -- 13.1.paste -- 13.2.sprintf -- 13.3. Extracting Text -- 13.4. Regular Expressions -- 13.5. Conclusion -- 14. Probability Distributions -- 14.1. Normal Distribution -- 14.2. Binomial Distribution -- 14.3. Poisson Distribution -- 14.4. Other Distributions -- 14.5. Conclusion -- 15. Basic Statistics--
  • 15.1. Summary Statistics -- 15.2. Correlation and Covariance -- 15.3.T-Tests -- 15.4. ANOVA -- 15.5. Conclusion -- 16. Linear Models -- 16.1. Simple Linear Regression -- 16.2. Multiple Regression -- 16.3. Conclusion -- 17. Generalized Linear Models -- 17.1. Logistic Regression -- 17.2. Poisson Regression -- 17.3. Other Generalized Linear Models -- 17.4. Survival Analysis -- 17.5. Conclusion -- 18. Model Diagnostics -- 18.1. Residuals -- 18.2.Comparing Models -- 18.3. Cross-Validation -- 18.4. Bootstrap -- 18.5. Stepwise Variable Selection -- 18.6. Conclusion -- 19. Regularization and Shrinkage -- 19.1. Elastic Net -- 19.2. Bayesian Shrinkage -- 19.3. Conclusion -- 20. Nonlinear Models -- 20.1. Nonlinear Least Squares -- 20.2. Splines -- 20.3. Generalized Additive Models -- 20.4. Decision Trees -- 20.5. Random Forests -- 20.6. Conclusion -- 21. Time Series and Autocorrelation -- 21.1. Autoregressive Moving Average -- 21.2. VAR -- 21.3. GARCH -- 21.4. Conclusion -- 22. Clustering--
  • 22.1.K-means -- 22.2. PAM -- 22.3. Hierarchical Clustering -- 22.4. Conclusion -- 23. Reproducibility, Reports and Slide Shows with knitr -- 23.1. Installing LATEX Program -- 23.2. LATEX Primer -- 23.3. Using knitr with LATEX -- 23.4. Markdown Tips -- 23.5. Using knitr and Markdown -- 23.6.pandoc -- 23.7. Conclusion -- 24. Building R Packages -- 24.1. Folder Structure -- 24.2. Package Files -- 24.3. Package Documentation -- 24.4. Checking, Building and Installing -- 24.5. Submitting to CRAN -- 24.6.C++ Code -- 24.7. Conclusion -- A. Real-Life Resources -- A.1. Meetups -- A.2. Stackoverflow -- A.3. Twitter -- A.4. Conferences -- A.5. Web Sites -- A.6. Documents -- A.7. Books -- A.8. Conclusion -- B. Glossary
Dimensions
24 cm.
Extent
xxi, 432 pages
Isbn
9780133257175
Lccn
2013027407
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations, maps
System control number
  • (OCoLC)852681998
  • (OCoLC)ocn852681998
Label
R for Everyone : Advanced Analytics and Graphics, Jared P. Lander
Publication
Bibliography note
Includes bibliographical references and indexes
Carrier category
volume
Carrier category code
nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Machine generated contents note: 1. Getting R -- 1.1. Downloading R -- 1.2.R Version -- 1.3.32-bit versus 64-bit -- 1.4. Installing -- 1.5. Revolution R Community Edition -- 1.6. Conclusion -- 2. The R Environment -- 2.1.Command Line Interface -- 2.2. RStudio -- 2.3. Revolution Analytics RPE -- 2.4. Conclusion -- 3.R Packages -- 3.1. Installing Packages -- 3.2. Loading Packages -- 3.3. Building a Package -- 3.4. Conclusion -- 4. Basics of R -- 4.1. Basic Math -- 4.2. Variables -- 4.3. Data Types -- 4.4. Vectors -- 4.5. Calling Functions -- 4.6. Function Documentation -- 4.7. Missing Data -- 4.8. Conclusion -- 5. Advanced Data Structures -- 5.1.data.frames -- 5.2. Lists -- 5.3. Matrices -- 5.4. Arrays -- 5.5. Conclusion -- 6. Reading Data into R -- 6.1. Reading CSVs -- 6.2. Excel Data -- 6.3. Reading from Databases -- 6.4. Data from Other Statistical Tools -- 6.5.R Binary Files -- 6.6. Data Included with R -- 6.7. Extract Data from Web Sites -- 6.8. Conclusion--
  • 7. Statistical Graphics -- 7.1. Base Graphics -- 7.2.ggplot2 -- 7.3. Conclusion -- 8. Writing R Functions -- 8.1. Hello, World! -- 8.2. Function Arguments -- 8.3. Return Values -- 8.4.do. call -- 8.5. Conclusion -- 9. Control Statements -- 9.1. If and else -- 9.2.switch -- 9.3.ifelse -- 9.4.Compound Tests -- 9.5. Conclusion -- 10. Loops, the Un-R Way to Iterate -- 10.1. For Loops -- 10.2. While Loops -- 10.3. Controlling Loops -- 10.4. Conclusion -- 11. Group Manipulation -- 11.1. Apply Family -- 11.2.aggregate -- 11.3.plyr -- 11.4.data.table -- 11.5. Conclusion -- 12. Data Reshaping -- 12.1.cbind and rbind -- 12.2. Joins -- 12.3.reshape2 -- 12.4. Conclusion -- 13. Manipulating Strings -- 13.1.paste -- 13.2.sprintf -- 13.3. Extracting Text -- 13.4. Regular Expressions -- 13.5. Conclusion -- 14. Probability Distributions -- 14.1. Normal Distribution -- 14.2. Binomial Distribution -- 14.3. Poisson Distribution -- 14.4. Other Distributions -- 14.5. Conclusion -- 15. Basic Statistics--
  • 15.1. Summary Statistics -- 15.2. Correlation and Covariance -- 15.3.T-Tests -- 15.4. ANOVA -- 15.5. Conclusion -- 16. Linear Models -- 16.1. Simple Linear Regression -- 16.2. Multiple Regression -- 16.3. Conclusion -- 17. Generalized Linear Models -- 17.1. Logistic Regression -- 17.2. Poisson Regression -- 17.3. Other Generalized Linear Models -- 17.4. Survival Analysis -- 17.5. Conclusion -- 18. Model Diagnostics -- 18.1. Residuals -- 18.2.Comparing Models -- 18.3. Cross-Validation -- 18.4. Bootstrap -- 18.5. Stepwise Variable Selection -- 18.6. Conclusion -- 19. Regularization and Shrinkage -- 19.1. Elastic Net -- 19.2. Bayesian Shrinkage -- 19.3. Conclusion -- 20. Nonlinear Models -- 20.1. Nonlinear Least Squares -- 20.2. Splines -- 20.3. Generalized Additive Models -- 20.4. Decision Trees -- 20.5. Random Forests -- 20.6. Conclusion -- 21. Time Series and Autocorrelation -- 21.1. Autoregressive Moving Average -- 21.2. VAR -- 21.3. GARCH -- 21.4. Conclusion -- 22. Clustering--
  • 22.1.K-means -- 22.2. PAM -- 22.3. Hierarchical Clustering -- 22.4. Conclusion -- 23. Reproducibility, Reports and Slide Shows with knitr -- 23.1. Installing LATEX Program -- 23.2. LATEX Primer -- 23.3. Using knitr with LATEX -- 23.4. Markdown Tips -- 23.5. Using knitr and Markdown -- 23.6.pandoc -- 23.7. Conclusion -- 24. Building R Packages -- 24.1. Folder Structure -- 24.2. Package Files -- 24.3. Package Documentation -- 24.4. Checking, Building and Installing -- 24.5. Submitting to CRAN -- 24.6.C++ Code -- 24.7. Conclusion -- A. Real-Life Resources -- A.1. Meetups -- A.2. Stackoverflow -- A.3. Twitter -- A.4. Conferences -- A.5. Web Sites -- A.6. Documents -- A.7. Books -- A.8. Conclusion -- B. Glossary
Dimensions
24 cm.
Extent
xxi, 432 pages
Isbn
9780133257175
Lccn
2013027407
Media category
unmediated
Media MARC source
rdamedia
Media type code
n
Other physical details
illustrations, maps
System control number
  • (OCoLC)852681998
  • (OCoLC)ocn852681998

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