Spatial Synthesis: Computational Social Science and Humanities, Ye Xinyue, Lin Hui

Автор: M. Antonia Amaral Turkman, Carlos Daniel Paulino, Peter Muller
Название: Computational Bayesian Statistics: An Introduction
ISBN: 1108481035 ISBN-13(EAN): 9781108481038
Издательство: Cambridge Academ
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Цена: 116160.00 T
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Описание: This book explains the fundamental ideas of Bayesian analysis, with a focus on computational methods such as MCMC and available software such as R/R-INLA, OpenBUGS, JAGS, Stan, and BayesX. It is suitable as a textbook for a first graduate-level course and as a user`s guide for researchers and graduate students from beyond statistics.

Автор: Ye Xinyue, Lin Hui
Название: Spatial Synthesis: Computational Social Science and Humanities
ISBN: 3030527336 ISBN-13(EAN): 9783030527334
Издательство: Springer
Цена: 46570.00 T
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Описание: This book describes how powerful computing technology, emerging big and open data sources, and theoretical perspectives on spatial synthesis have revolutionized the way in which we investigate social sciences and humanities.

Автор: IAN N. GREGORY
Название: Toward Spatial Humanities: Historical GIS and Spatial History
ISBN: 0253011868 ISBN-13(EAN): 9780253011862
Издательство: Wiley EDC
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Цена: 27450.00 T
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Описание: The application of Geographic Information Systems (GIS) to issues in history is among the most exciting developments in both digital and spatial humanities. Describing a wide variety of applications, the essays in this volume highlight the methodological and substantive implications of a spatial approach to history. They illustrate how the use of GIS is changing our understanding of the geographies of the past and has become the basis for new ways to study history. Contributors focus on current developments in the use of historical sources and explore the insights gained by applying GIS to develop historiography. Toward Spatial Humanities is a compelling demonstration of how GIS can contribute to our historical understanding.

Автор: Cioffi-revilla, Claudio
Название: Introduction to computational social science
ISBN: 3319843249 ISBN-13(EAN): 9783319843247
Издательство: Springer
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Цена: 79190.00 T
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Описание: This effective introduction to the key concepts in computational social science includes formal definitions and a glossary, covers topics such as information extraction, social networks and complexity theory, and discusses a range of methodological tools.

Автор: Mcclarren, Ryan G.
Название: Uncertainty quantification and predictive computational science
ISBN: 3319995243 ISBN-13(EAN): 9783319995243
Издательство: Springer
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Цена: 93160.00 T
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Описание: This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties.

Название: Multi-Dimensional Analysis
ISBN: 1350023825 ISBN-13(EAN): 9781350023826
Издательство: Bloomsbury Academic
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Цена: 137280.00 T
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Multi-dimensional Analysis: Research Methods and Current Issues provides a comprehensive guide both to the statistical methods in Multi-dimensional Analysis (MDA) and its key elements, such as corpus building, tagging, and tools. The major goal is to explain the steps involved in the method so that readers may better understand this complex research framework and conduct MD research on their own.

Multi-dimensional Analysis is a method that allows the researcher to describe different registers (textual varieties defined by their social use) such as academic settings, regional discourse, social media, movies, and pop songs. Through multivariate statistical techniques, MDA identifies complementary correlation groupings of dozens of variables, including variables which belong both to the grammatical and semantic domains. Such groupings are then associated with situational variables of texts like information density, orality, and narrativity to determine linguistic constructs known as dimensions of variation, which provide a scale for the comparison of a large number of texts and registers.

This book is a comprehensive research guide to MDA.

Автор: Cairns Paul
Название: Doing Better Statistics in Human-Computer Interaction
ISBN: 110871059X ISBN-13(EAN): 9781108710596
Издательство: Cambridge Academ
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Цена: 33790.00 T
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Описание: Written for human-computer interaction (HCI) researchers - whether undergraduates, professors, or UX professionals who need to analyse quantitative data - this book helps to improve readers` knowledge of the modern best practice in statistics and their understanding of how to do statistical analysis on their own data.

Автор: Arnold
Название: A Computational Approach to Statistical Learning
ISBN: 113804637X ISBN-13(EAN): 9781138046375
Издательство: Taylor&Francis
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Цена: 83690.00 T
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Описание: A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal working implementations of common statistical learning algorithms. Every chapter concludes with a fully worked out application that illustrates predictive modeling tasks using a real-world dataset. The text begins with a detailed analysis of linear models and ordinary least squares. Subsequent chapters explore extensions such as ridge regression, generalized linear models, and additive models. The second half focuses on the use of general-purpose algorithms for convex optimization and their application to tasks in statistical learning. Models covered include the elastic net, dense neural networks, convolutional neural networks (CNNs), and spectral clustering. A unifying theme throughout the text is the use of optimization theory in the description of predictive models, with a particular focus on the singular value decomposition (SVD). Through this theme, the computational approach motivates and clarifies the relationships between various predictive models. Taylor Arnold is an assistant professor of statistics at the University of Richmond. His work at the intersection of computer vision, natural language processing, and digital humanities has been supported by multiple grants from the National Endowment for the Humanities (NEH) and the American Council of Learned Societies (ACLS). His first book, Humanities Data in R, was published in 2015. Michael Kane is an assistant professor of biostatistics at Yale University. He is the recipient of grants from the National Institutes of Health (NIH), DARPA, and the Bill and Melinda Gates Foundation. His R package bigmemory won the Chamber's prize for statistical software in 2010. Bryan Lewis is an applied mathematician and author of many popular R packages, including irlba, doRedis, and threejs.

Автор: Uwe Engel, Anabel Quan-Haase, Sunny Xun
Название: Handbook of Computational Social Science, Volume 1
ISBN: 0367456524 ISBN-13(EAN): 9780367456528
Издательство: Taylor&Francis
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Цена: 58170.00 T
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Описание: The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches.

Автор: Uwe Engel, Anabel Quan-Haase, Sunny Xun
Название: Handbook of Computational Social Science, Volume 2
ISBN: 1032077700 ISBN-13(EAN): 9781032077703
Издательство: Taylor&Francis
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Цена: 58170.00 T
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Описание: The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches.

Автор: Ulrich R?de
Название: Mathematical and Computational Techniques for Multilevel Adaptive Methods
ISBN: 089871320X ISBN-13(EAN): 9780898713206
Издательство: Mare Nostrum (Eurospan)
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Цена: 53510.00 T
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Описание: Introduces a well-founded mathematical theory that leads to intelligent, adaptive algorithms, and suggests advanced software techniques. This new kind of multigrid theory supports the so-called "BPX" and "multilevel Schwarz" methods, and leads to the discovery of faster more robust algorithms.

Автор: Okabe
Название: Spatial Analysis Along Networks - Statistical and Computational Methods
ISBN: 0470770813 ISBN-13(EAN): 9780470770818
Издательство: Wiley
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Цена: 88650.00 T
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Описание: * Presents a much-needed practical guide to statistical spatial analysis on a network, in a logical, user-friendly order. * Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics.