Network Analysis With R Igraph

Computational Network Analysis With R: Applications in Biology, Medicine and Chemistry  eBooks & eLearning

Posted by Underaglassmoon at Sept. 24, 2016
Computational Network Analysis With R: Applications in Biology, Medicine and Chemistry

Computational Network Analysis With R: Applications in Biology, Medicine and Chemistry
Wiley VCH | Biology | Oct 3 2016 | ISBN-10: 3527339582 | 368 pages | pdf | 19.92 mb

by Matthias Dehmer (Author), Yongtang Shi (Editor), Frank Emmert-streib (Editor)

A User's Guide to Network Analysis in R  eBooks & eLearning

Posted by interes at March 7, 2016
A User's Guide to Network Analysis in R

A User's Guide to Network Analysis in R by Douglas A. Luke
English | 2016 | ISBN: 3319238825 | 238 pages | EPUB | 8,8 MB

A User's Guide to Network Analysis in R  eBooks & eLearning

Posted by Underaglassmoon at Dec. 16, 2015
A User's Guide to Network Analysis in R

A User's Guide to Network Analysis in R
Springer | Mathematics | January 6, 2016 | ISBN-10: 3319238825 | 238 pages | pdf | 6.6 mb

Authors: Luke, Douglas A.
Provides a practical, hands-on tour of the major network analytic tasks R is capable of, including network data management, network visualization, network description, and network modeling
Includes all R code needed for examples used throughout the book
Serves as an excellent reference resource for teaching and learning network science, analytics, and techniques

Social Network Analysis Using R  eBooks & eLearning

Posted by naag at Jan. 5, 2017
Social Network Analysis Using R

Social Network Analysis Using R
MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 1 Hours | 133 MB
Genre: eLearning | Language: English

Statistical Analysis of Network Data with R (repost)  eBooks & eLearning

Posted by interes at Sept. 15, 2014
Statistical Analysis of Network Data with R (repost)

Statistical Analysis of Network Data with R (Use R!) by Eric D. Kolaczyk and Gábor Csárdi
English | 2014 | ISBN-10: 1493909827 | 207 pages | PDF | 5 MB

Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries.

Statistical Analysis of Network Data with R  eBooks & eLearning

Posted by arundhati at June 13, 2014
Statistical Analysis of Network Data with R

Eric D. Kolaczyk, Gábor Csárdi, "Statistical Analysis of Network Data with R"
2014 | ISBN-10: 1493909827 | 207 pages | PDF | 5 MB

Introduction to Data Analysis with R for Forensic Scientists (Repost)  eBooks & eLearning

Posted by roxul at Dec. 15, 2016
Introduction to Data Analysis with R for Forensic Scientists (Repost)

James Michael Curran, "Introduction to Data Analysis with R for Forensic Scientists"
English | ISBN: 1420088262 | 2010 | 331 pages | PDF | 13 MB

Event History Analysis with R (Repost)  eBooks & eLearning

Posted by nebulae at Dec. 14, 2016
Event History Analysis with R (Repost)

Göran Broström, "Event History Analysis with R"
English | ISBN: 1439831645 | 2012 | 236 pages | PDF | 3 MB
Dianne Cook, Deborah F. Swayne - Interactive and Dynamic Graphics for Data Analysis: With R and GGobi [Repost]

Dianne Cook, Deborah F. Swayne - Interactive and Dynamic Graphics for Data Analysis: With R and GGobi
2007 | ISBN: 0387717617 | English | 190 pages | PDF | 5.2 MB

Pluralsight - Exploratory Data Analysis with R [repost]  eBooks & eLearning

Posted by house23 at Oct. 9, 2016
Pluralsight - Exploratory Data Analysis with R [repost]

Pluralsight - Exploratory Data Analysis with R
MP4 | AVC 426kbps | English | 1024x768 | 15fps | 2h 29mins | AAC stereo 79kbps | 422 MB
Genre: Video Training

R is a popular open-source programming language for data analysis. Its interactive programming environment and data visualization capabilities make R an ideal tool for exploratory data analysis. This course will provide an introduction to the R programming language and demonstrate how R can be used for exploratory data analysis to complete day-to-day developer tasks.