From Experimental Network to Meta-analysis

From Experimental Network to Meta-analysis PDF Author: David Makowski
Publisher: Springer
ISBN: 940241696X
Category : Technology & Engineering
Languages : en
Pages : 155

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Book Description
This book has been designed as a methodological guide and shows the interests and limitations of different statistical methods to analyze data from experimental networks and to perform meta-analyses. It is intended for engineers, students and researchers involved in data analysis in agronomy and environmental science.

From Experimental Network to Meta-analysis

From Experimental Network to Meta-analysis PDF Author: David Makowski
Publisher: Springer
ISBN: 940241696X
Category : Technology & Engineering
Languages : en
Pages : 155

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Book Description
This book has been designed as a methodological guide and shows the interests and limitations of different statistical methods to analyze data from experimental networks and to perform meta-analyses. It is intended for engineers, students and researchers involved in data analysis in agronomy and environmental science.

Advanced Network Analysis Techniques

Advanced Network Analysis Techniques PDF Author: Laura Chappell
Publisher:
ISBN: 9781893939288
Category : Computer networks
Languages : en
Pages : 0

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Book Description


Advanced Methods for Complex Network Analysis

Advanced Methods for Complex Network Analysis PDF Author: Meghanathan, Natarajan
Publisher: IGI Global
ISBN: 1466699655
Category : Computers
Languages : en
Pages : 484

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Book Description
As network science and technology continues to gain popularity, it becomes imperative to develop procedures to examine emergent network domains, as well as classical networks, to help ensure their overall optimization. Advanced Methods for Complex Network Analysis features the latest research on the algorithms and analysis measures being employed in the field of network science. Highlighting the application of graph models, advanced computation, and analytical procedures, this publication is a pivotal resource for students, faculty, industry practitioners, and business professionals interested in theoretical concepts and current developments in network domains.

Network Analysis Techniques

Network Analysis Techniques PDF Author: S. K. Bhatnagar
Publisher: Prentice Hall
ISBN:
Category : Business & Economics
Languages : en
Pages : 280

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Book Description
This book deals with various techniques that use basic concepts of preparation and analysis of networks for planning, scheduling and control of Projects.

Social Network Analysis

Social Network Analysis PDF Author: Song Yang
Publisher: SAGE Publications, Incorporated
ISBN: 9781483325217
Category : Social Science
Languages : en
Pages : 0

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Book Description
Social Network Analysis: Methods and Examples by Song Yang, Franziska B. Keller, and Lu Zheng prepares social science students to conduct their own social network analysis (SNA) by covering basic methodological tools along with illustrative examples from various fields. This innovative book takes a conceptual rather than a mathematical approach as it discusses the connection between what SNA methods have to offer and how those methods are used in research design, data collection, and analysis. Four substantive applications chapters provide examples from politics, work and organizations, mental and physical health, and crime and terrorism studies.

Python for Graph and Network Analysis

Python for Graph and Network Analysis PDF Author: Mohammed Zuhair Al-Taie
Publisher: Springer
ISBN: 3319530046
Category : Computers
Languages : en
Pages : 214

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Book Description
This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse and process data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber security, business, animal social networks, information retrieval, and communications.

Challenges in Social Network Research

Challenges in Social Network Research PDF Author: Giancarlo Ragozini
Publisher: Springer Nature
ISBN: 3030314634
Category : Computers
Languages : en
Pages : 245

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Book Description
The book includes both invited and contributed chapters dealing with advanced methods and theoretical development for the analysis of social networks and applications in numerous disciplines. Some authors explore new trends related to network measures, multilevel networks and clustering on networks, while other contributions deepen the relationship among statistical methods for data mining and social network analysis. Along with the new methodological developments, the book offers interesting applications to a wide set of fields, ranging from the organizational and economic studies, collaboration and innovation, to the less usual field of poetry. In addition, the case studies are related to local context, showing how the substantive reasoning is fundamental in social network analysis. The list of authors includes both top scholars in the field of social networks and promising young researchers. All chapters passed a double blind review process followed by the guest editors. This edited volume will appeal to students, researchers and professionals.

Network Analysis and Synthesis

Network Analysis and Synthesis PDF Author: Brian D. O. Anderson
Publisher: Courier Corporation
ISBN: 0486152170
Category : Technology & Engineering
Languages : en
Pages : 559

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Book Description
This comprehensive look at linear network analysis and synthesis explores state-space synthesis as well as analysis, employing modern systems theory to unite classical concepts of network theory. 1973 edition.

A User’s Guide to Network Analysis in R

A User’s Guide to Network Analysis in R PDF Author: Douglas Luke
Publisher: Springer
ISBN: 3319238833
Category : Mathematics
Languages : en
Pages : 241

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Book Description
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 in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.

Scalable Algorithms for Data and Network Analysis

Scalable Algorithms for Data and Network Analysis PDF Author: Shang-Hua Teng
Publisher:
ISBN: 9781680831306
Category : Computers
Languages : en
Pages : 292

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Book Description
In the age of Big Data, efficient algorithms are in high demand. It is also essential that efficient algorithms should be scalable. This book surveys a family of algorithmic techniques for the design of scalable algorithms. These techniques include local network exploration, advanced sampling, sparsification, and geometric partitioning.