Statistical Analysis of Network Data with R 2/e
暫譯: 使用 R 進行網路數據的統計分析（第二版）

Kolaczyk, Eric D., Csárdi, Gábor

Statistical Analysis of Network Data with R 2/e
  • 出版商: Springer
  • 出版日期: 2020-06-03
  • 售價: $3,530
  • 貴賓價: 9.5 折 $3,354
  • 語言: 英文
  • 頁數: 228
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3030441288
  • ISBN-13: 9783030441289

    • 海外代購書籍(需單獨結帳)

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商品描述

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 analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. The new edition of this book includes an overhaul to recent changes in igraph. The material in this book is organized to flow from descriptive statistical methods to topics centered on modeling and inference with networks, with the latter separated into two sub-areas, corresponding first to the modeling and inference of networks themselves, and then, to processes on networks.

The book begins by covering tools for the manipulation of network data. Next, it addresses visualization and characterization of networks. The book then examines mathematical and statistical network modeling. This is followed by a special case of network modeling wherein the network topology must be inferred. Network processes, both static and dynamic are addressed in the subsequent chapters. The book concludes by featuring chapters on network flows, dynamic networks, and networked experiments. Statistical Analysis of Network Data with R, 2nd Ed. has been written at a level aimed at graduate students and researchers in quantitative disciplines engaged in the statistical analysis of network data, although advanced undergraduates already comfortable with R should find the book fairly accessible as well.

商品描述(中文翻譯)

這本書的新版本提供了一個易於理解的介紹，使用 R 進行網路數據的統計分析。它已經全面修訂，可以作為一個獨立的資源，使用多個 R 套件來說明如何進行各種網路分析，從基本的操作和視覺化，到摘要和特徵描述，再到網路數據的建模。核心套件是 igraph，它提供了在 R 中研究網路圖的廣泛功能。本書的新版本包括對 igraph 最近變更的全面更新。本書的內容組織從描述性統計方法流向以網路為中心的建模和推斷主題，後者又分為兩個子領域，首先是網路本身的建模和推斷，其次是網路上的過程。

本書首先涵蓋了網路數據的操作工具。接下來，討論了網路的視覺化和特徵描述。然後，本書檢視了數學和統計網路建模。隨後是網路建模的一個特例，其中必須推斷網路拓撲。接下來的章節將探討靜態和動態的網路過程。本書最後以網路流、動態網路和網路實驗的章節作結。《Statistical Analysis of Network Data with R, 2nd Ed.》的寫作水平針對從事網路數據統計分析的定量學科的研究生和研究人員，儘管已經熟悉 R 的高年級本科生也應該能夠相對輕鬆地理解本書。

作者簡介

 

Eric D. Kolaczyk is a professor of statistics and a data science faculty fellow at Boston University, in the Department of Mathematics and Statistics, where he also is an affiliated faculty member in the Bioinformatics Program, the Division of Systems Engineering, and the Center for Systems Neuroscience. Currently, he serves as the director of Boston University's Hariri Institute for Computing. His publications on network-based topics, beyond the development of statistical methodology and theory, include work on applications ranging from the detection of anomalous traffic patterns in computer networks to the prediction of biological function in networks of interacting proteins to the characterization of influence of groups of actors in social networks. He is an elected fellow of the American Association for the Advancement of Science (AAAS), the American Statistical Association (ASA), and the Institute of Mathematical Statistics, an elected member of the International Statistical Institute (ISI), and an elected senior member of the Institute of Electrical and Electronics Engineers (IEEE).

 

Gábor Csárdi is a software engineer at RStudio, where he works on R infrastructure packages. He holds a PhD in Computer Science from Eötvös University, Hungary, and he has done postdocs at the Swiss Institute of Bioinformatics, the University of Lausanne, and Harvard University.

 

 

 

 

作者簡介(中文翻譯)

Eric D. Kolaczyk 是波士頓大學數學與統計系的統計學教授及數據科學教職員，並且是生物資訊學程、系統工程部門及系統神經科學中心的附屬教職員。目前，他擔任波士頓大學哈里里計算研究所的所長。他在基於網絡的主題上的出版物，除了統計方法和理論的發展外，還包括從檢測計算機網絡中的異常流量模式到預測互動蛋白質網絡中的生物功能，再到描述社交網絡中行為者群體影響力的應用。他是美國科學促進會（AAAS）、美國統計協會（ASA）和數學統計學會的當選會士，國際統計學會（ISI）的當選成員，以及電氣和電子工程師學會（IEEE）的當選高級會員。

Gábor Csárdi 是 RStudio 的軟體工程師，專注於 R 基礎設施套件。他擁有匈牙利厄爾特大學的計算機科學博士學位，並曾在瑞士生物資訊學研究所、洛桑大學和哈佛大學進行博士後研究。

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