Statistical Analysis of Network Data

This book PDF is perfect for those who love Computers genre, written by Eric D. Kolaczyk and published by Springer Science & Business Media which was released on 20 April 2009 with total hardcover pages 397. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Statistical Analysis of Network Data books below.

Statistical Analysis of Network Data
Author : Eric D. Kolaczyk
File Size : 40,9 Mb
Publisher : Springer Science & Business Media
Language : English
Release Date : 20 April 2009
ISBN : 9780387881461
Pages : 397 pages
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Statistical Analysis of Network Data by Eric D. Kolaczyk Book PDF Summary

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 from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.

Statistical Analysis of Network Data

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

Get Book
Statistical Analysis of Network Data with R

The new edition of this book provides an easily accessible introduction to the statistical analysis of network data using R. It has been fully revised and can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network

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Statistical Analysis of Network Data with R

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

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Probabilistic Foundations of Statistical Network Analysis

Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power

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Statistical and Machine Learning Approaches for Network Analysis

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data,

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A Survey of Statistical Network Models

Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models

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Hands On Network Forensics

Gain basic skills in network forensics and learn how to apply them effectively Key FeaturesInvestigate network threats with easePractice forensics tasks such as intrusion detection, network analysis, and scanningLearn forensics investigation at the network levelBook Description Network forensics is a subset of digital forensics that deals with network attacks and

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Models for Social Networks With Statistical Applications

The study of social networks is a new but fast widening multidisciplinary area involving social, mathematical, statistical and computer sciences for application in diverse social environments; in the latter sciences, and specially for the field of Economics. It has its own parameters and methodological tools. In 'Models for Social Networks

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