Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector spatial filtering (MESF) technique. MESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in their georeferenced data analyses. Its appeal is in its simplicity, yet its implementation drawbacks include serious complexities associated with constructing an eigenvector spatial filter. This book discusses MESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, space-time models, and spatial interaction models. Spatial Regression Analysis Using Eigenvector Spatial Filtering is accompanied by sample R codes and a Windows application with illustrative datasets so that readers can replicate the examples in the book and apply the methodology to their own application projects. It also includes a Foreword by Pierre Legendre.

Spatial Regression Analysis Using Eigenvector Spatial Filtering

Business & Money

Griffith, Daniel

Chun, Yongwan

Li, Bin

Economics

Academic Press

Protection Technologies of Ultra-High-Voltage AC Transmission Systems considers the latest research on UHV, UHV transmission line electromagnetic field, transmission line parameters, and tower structures, with a focus on protective relaying of UHV transmission systems. This book gives insights into protective relaying of UHV AC transmission systems and sheds light on the conundrum of protective relaying for the EHV systems. In addition, it elaborates on both traditional relaying and the application of new type current differential protection, distance protection and automatic reclosing, as well as protective schemes for transformers and reactors in UHV transmission systems. This resource will serve as an important reference for technical personnel in network design and operation, as well as students and engineers in related engineering areas.

Protection Technologies of Ultra-High-Voltage AC Transmission Systems

Engineering & Transportation

Li, Yongli

He, Jiali

Zheng, Yuping

Engineering

Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS (Chapman & Hall/CRC Biostatistics Series)

Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers. 
Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Using this method, multiple third- variables of different types can be considered simultaneously, and the indirect effect carried by individual third-variables can be separated from the total effect. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis. 
Key Features: Parametric and nonparametric method in third variable analysis Multivariate and Multiple third-variable effect analysis Multilevel mediation/confounding analysis Third-variable effect analysis with high-dimensional data Moderation/Interaction effect analysis within the third-variable analysis R packages and SAS macros to implement methods proposed in the book

Health, Fitness & Dieting

Yu, Qingzhao

Diseases & Physical Ailments

Chapman and Hall/CRC

Digital Technology and Justice

Justice apps – mobile and web-based programmes that can assist individuals with legal tasks – are being produced, improved, and accessed at an unprecedented rate. These technologies have the potential to reshape the justice system, improve access to justice, and demystify legal institutions. Using artificial intelligence techniques, apps can even facilitate the resolution of common legal disputes. 
However, these opportunities must be assessed in light of the many challenges associated with app use in the justice sector. These include the digital divide and other accessibility issues; the ethical challenges raised by the dehumanisation of legal processes; and various privacy, security, and confidentiality risks. 
Surveying the landscape of this emergent industry, this book explores the objectives, opportunities, and challenges presented by apps across all areas of the justice sector. Detailed consideration is also given to the use of justice apps in specific legal contexts, including the family law and criminal law sectors. The first book to engage with justice apps, this book will appeal to a wide range of legal scholars, students, practitioners, and policy-makers.

Computers & Technology

Sourdin, Tania

Meredith, Jacqueline

Computer Science

Routledge

Spatial Autocorrelation: A Fundamental Property of Geospatial Phenomena

Science & Math

Earth Sciences

Elsevier

This book introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis.

Online Portfolio Selection: Principles and Algorithms

With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment.The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that:    Introduce OLPS and formulate OLPS as a sequential decision task Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art Investigate possible future directions  Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment.Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.

Online Portfolio Selection

Hoi, Steven Chu Hong

CRC-Press

With the aim to sequentially determine optimal allocations across a set of assets, Online Portfolio Selection (OLPS) has significantly reshaped the financial investment landscape. Online Portfolio Selection: Principles and Algorithms supplies a comprehensive survey of existing OLPS principles and presents a collection of innovative strategies that leverage machine learning techniques for financial investment. The book presents four new algorithms based on machine learning techniques that were designed by the authors, as well as a new back-test system they developed for evaluating trading strategy effectiveness. The book uses simulations with real market data to illustrate the trading strategies in action and to provide readers with the confidence to deploy the strategies themselves. The book is presented in five sections that: <ol>
<li>Introduce OLPS and formulate OLPS as a sequential decision task</li> <li>Present key OLPS principles, including benchmarks, follow the winner, follow the loser, pattern matching, and meta-learning</li> <li>Detail four innovative OLPS algorithms based on cutting-edge machine learning techniques</li> <li>Provide a toolbox for evaluating the OLPS algorithms and present empirical studies comparing the proposed algorithms with the state of the art</li> <li>Investigate possible future directions</li> </ol>
Complete with a back-test system that uses historical data to evaluate the performance of trading strategies, as well as MATLAB® code for the back-test systems, this book is an ideal resource for graduate students in finance, computer science, and statistics. It is also suitable for researchers and engineers interested in computational investment. Readers are encouraged to visit the authors’ website for updates: http://olps.stevenhoi.org.

Luzhou Laojiao: Chinese Baijiu in Comics

Cookbooks, Food & Wine

Yang, Jianhui

Regional & International

Royal Collins Publishing Company

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Books by Li, Bin