An Introduction To Exponential Random Graph Modeling
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An Introduction To Exponential Random Graph Modeling
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Author : Jenine K. Harris
language : en
Publisher: SAGE Publications
Release Date : 2013-12-23
An Introduction To Exponential Random Graph Modeling written by Jenine K. Harris and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-23 with Social Science categories.
This volume introduces the basic concepts of Exponential Random Graph Modeling (ERGM), gives examples of why it is used, and shows the reader how to conduct basic ERGM analyses in their own research. ERGM is a statistical approach to modeling social network structure that goes beyond the descriptive methods conventionally used in social network analysis. Although it was developed to handle the inherent non-independence of network data, the results of ERGM are interpreted in similar ways to logistic regression, making this a very useful method for examining social systems. Recent advances in statistical software have helped make ERGM accessible to social scientists, but a concise guide to using ERGM has been lacking. This book fills that gap, by using examples from public health, and walking the reader through the process of ERGM model-building using R statistical software and the statnet package. An Introduction to Exponential Random Graph Modeling is a part of SAGE’s Quantitative Applications in the Social Sciences (QASS) series, which has helped countless students, instructors, and researchers learn cutting-edge quantitative techniques.
Exponential Random Graph Models For Social Networks
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Author : Dean Lusher
language : en
Publisher: Cambridge University Press
Release Date : 2013
Exponential Random Graph Models For Social Networks written by Dean Lusher and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Business & Economics categories.
This book provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs).
An Introduction To Exponential Random Graph Modeling
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Author : Jenine K. Harris
language : en
Publisher: SAGE Publications
Release Date : 2013-12-23
An Introduction To Exponential Random Graph Modeling written by Jenine K. Harris and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-23 with Social Science categories.
This volume introduces the basic concepts of Exponential Random Graph Modeling (ERGM), gives examples of why it is used, and shows the reader how to conduct basic ERGM analyses in their own research. ERGM is a statistical approach to modeling social network structure that goes beyond the descriptive methods conventionally used in social network analysis. Although it was developed to handle the inherent non-independence of network data, the results of ERGM are interpreted in similar ways to logistic regression, making this a very useful method for examining social systems. Recent advances in statistical software have helped make ERGM accessible to social scientists, but a concise guide to using ERGM has been lacking. An Introduction to Exponential Random Graph Modeling, by Jenine K. Harris, fills that gap, by using examples from public health, and walking the reader through the process of ERGM model-building using R statistical software and the statnet package.
Inferential Network Analysis
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Author : Skyler J. Cranmer
language : en
Publisher: Cambridge University Press
Release Date : 2020-11-19
Inferential Network Analysis written by Skyler J. Cranmer and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-19 with Business & Economics categories.
Pioneering introduction of unprecedented breadth and scope to inferential and statistical methods for network analysis.
Random Graphs And Complex Networks
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Author : Remco van der Hofstad
language : en
Publisher: Cambridge University Press
Release Date : 2017
Random Graphs And Complex Networks written by Remco van der Hofstad and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Computers categories.
This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.
A Survey Of Statistical Network Models
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Author : Anna Goldenberg
language : en
Publisher: Now Publishers Inc
Release Date : 2010
A Survey Of Statistical Network Models written by Anna Goldenberg and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
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 on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.
Statistical Network Analysis Models Issues And New Directions
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Author : Edoardo M. Airoldi
language : en
Publisher: Springer
Release Date : 2008-04-12
Statistical Network Analysis Models Issues And New Directions written by Edoardo M. Airoldi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-12 with Computers categories.
This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Statistical Network Analysis: Models, Issues, and New Directions held in Pittsburgh, PA, USA in June 2006 as associated event of the 23rd International Conference on Machine Learning, ICML 2006. It covers probabilistic methods for network analysis, paying special attention to model design and computational issues of learning and inference.
Introduction To Random Graphs
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Author : Alan Frieze
language : en
Publisher: Cambridge University Press
Release Date : 2016
Introduction To Random Graphs written by Alan Frieze and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Mathematics categories.
The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.
Calculus
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Author : Gudmund R. Iversen
language : en
Publisher: SAGE
Release Date : 1996-01-18
Calculus written by Gudmund R. Iversen and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-01-18 with Mathematics categories.
Aimed at readers who may be more familiar with statistics than calculus and mathematics, this carefully written volume gives an overview of the central ideas in calculus. Author Gudmund R. Iversen shows examples of how calculus is used to translate many real-world phenomena into mathematical functions. Beginning with an explanation of the two major parts of calculus, differentiation and integration, Iversen illustrates how calculus is used in statistics to distinguish between the mean and the median, to derive the least squares formulas for regression coefficients, to find values of parameters from theoretical distributions, and to find a statistical p value when we using one of the continuous test variables like the t variable. Social scientists who either never took a calculus course or who want to "brush up" on their understanding of calculus will find this book a necessity.
Interrupted Time Series Analysis
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Author : David McDowall
language : en
Publisher: Oxford University Press
Release Date : 2019-09-16
Interrupted Time Series Analysis written by David McDowall and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-16 with Medical categories.
Interrupted Time Series Analysis develops a comprehensive set of models and methods for drawing causal inferences from time series. It provides example analyses of social, behavioral, and biomedical time series to illustrate a general strategy for building AutoRegressive Integrated Moving Average (ARIMA) impact models. Additionally, the book supplements the classic Box-Jenkins-Tiao model-building strategy with recent auxiliary tests for transformation, differencing, and model selection. Not only does the text discuss new developments, including the prospects for widespread adoption of Bayesian hypothesis testing and synthetic control group designs, but it makes optimal use of graphical illustrations in its examples. With forty completed example analyses that demonstrate the implications of model properties, Interrupted Time Series Analysis will be a key inter-disciplinary text in classrooms, workshops, and short-courses for researchers familiar with time series data or cross-sectional regression analysis but limited background in the structure of time series processes and experiments.