Statistical Analysis of Network Data with R

• Author : Douglas Luke
• Publisher : Springer
• Release Date : 2015-12-14
• ISBN : 9783319238838

Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books

• Author : Eric D. Kolaczyk,Gábor Csárdi
• Publisher : Springer
• Release Date : 2014-05-22
• ISBN : 9781493909834

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. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can

• Author : Alboukadel Kassambara
• Publisher : STHDA
• Release Date : 2017-11-26
• ISBN : 9781981179671

Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks. This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs. - Detect important or central entities in a network graph. - Detect community (or cluster) in a network.

• Author : Gençer, Mehmet
• Publisher : IGI Global
• Release Date : 2020-02-07
• ISBN : 9781799819141

Understanding the social relations within the fields of business and economics is vital for the promotion of success within a certain organization. Analytics and statistics have taken a prominent role in marketing and management practices as professionals are constantly searching for a competitive advantage. Converging these technological tools with traditional methods of business relations is a trending area of research. Applied Social Network Analysis With R: Emerging Research and Opportunities is an essential reference source that materializes and analyzes the

• Author : Stephen P. Borgatti,Martin G. Everett,Jeffrey C. Johnson,Filip Agneessens
• Publisher : SAGE
• Release Date : 2022-04-30
• ISBN : 9781529764925

This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: • Discusses measures and techniques for analyzing

• Author : Yanchang Zhao
• Publisher : Academic Press
• Release Date : 2012-12-31
• ISBN : 9780123972712

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis,

• Author : Eric D. Kolaczyk
• Publisher : Springer Science & Business Media
• Release Date : 2009-04-20
• ISBN : 9780387881461

In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and

• Author : Tony Fischetti,Brett Lantz,Jaynal Abedin,Hrishi V. Mittal,Bater Makhabel,Edina Berlinger,Ferenc Illes,Milan Badics,Adam Banai,Gergely Daroczi
• Publisher : Packt Publishing Ltd
• Release Date : 2016-06-24
• ISBN : 9781786460486

Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data

• Author : Alboukadel Kassambara
• Publisher : STHDA
• Release Date : 2017-11-14
• ISBN : 9781979748100

Data visualization is one of the most important part of data science. Many books and courses present a catalogue of graphics but they don't teach you which charts to use according to the type of the data. In this book, we start by presenting the key graphic systems and packages available in R, including R base graphs, lattice and ggplot2 plotting systems. Next, we provide more than 200 practical examples to create great graphics for the right data using either the

• Author : Gregg Hartvigsen
• Publisher : Columbia University Press
• Release Date : 2021-06-29
• ISBN : 9780231554404

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data. Drawing on Gregg Hartvigsen’s extensive experience teaching biostatistics and modeling biological systems, this text is an engaging, practical, and lab-oriented introduction to R for students in the life sciences. Underscoring the importance of R and RStudio in organizing, computing, and visualizing biological statistics and data, Hartvigsen guides readers through the processes of correctly entering and analyzing data and using R

• Author : Mathias Harrer,Pim Cuijpers,Toshi A. Furukawa,David D. Ebert
• Publisher : CRC Press
• Release Date : 2021-09-15
• ISBN : 9781000435634

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced

• Author : Tamara Munzner
• Publisher : CRC Press
• Release Date : 2014-12-01
• ISBN : 9781498759717

Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques

• Author : Ken Cherven
• Publisher : Packt Publishing Ltd
• Release Date : 2015-01-28
• ISBN : 9781783987351

This book is intended for anyone interested in advanced network analysis. If you wish to master the skills of analyzing and presenting network graphs effectively, then this is the book for you. No coding experience is required to use this book, although some familiarity with the Gephi user interface will be helpful.

• Author : Helen C. Purchase,Ignaz Rutter
• Publisher : Springer Nature
• Release Date : 2021-12-22
• ISBN : 9783030929312

This book constitutes the proceedings of the 28th International Symposium on Graph Drawing and Network Visualization, GD 2021, which was held in Tübingen, Germany, during September 14-17, 2021. The 23 full papers and 5 short papers presented in these proceedings were carefully reviewed and selected from 74 submissions. The abstracts of 13 posters presented at the conference can be found in the back matter of the volume. The contributions were organized in topical sections as follows: Best Paper (Track 1: Combinatorial and Algorithmic Aspects); Best Paper (

• Author : Michael Jünger,Petra Mutzel
• Publisher : Springer Science & Business Media
• Release Date : 2012-12-06
• ISBN : 9783642186387

After an introduction to the subject area and a concise treatment of the technical foundations for the subsequent chapters, this book features 14 chapters on state-of-the-art graph drawing software systems, ranging from general "tool boxes'' to customized software for various applications. These chapters are written by leading experts: they follow a uniform scheme and can be read independently from each other. The text covers many industrial applications.