Inference for Functional Data With Applications

AI framework intended to solve a problem of bias-variance tradeoff for supervised learning methods in real-life applications. It comprises of bootstrapping to create multiple training and testing

Introduction to Time Series Modeling: with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal

Introduction to Time Series Modeling: with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal

The engaging, self-guided way to learn how to write better in EnglishMastering English grammar can be a real challenge. But, with a little practice and patience, you can discover how to communicate be

Biology has entered the age of Big Data. A technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce comparisons of shape to a comparison of algebraic invariants, such as numbers, which are typically easier to work with. Topological data analysis is a rapidly developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer, and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolu

Your logical, linear guide to the fundamentals of data science programming Data science is exploding--in a good way--with a forecast of 1.7 megabytes of new information created every second for each h

With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for ad

The theory of semigroups of operators is one of the most important themes in modern analysis. Not only does it have great intellectual beauty, but also wide-ranging applications. In this book the author first presents the essential elements of the theory, introducing the notions of semigroup, generator and resolvent, and establishes the key theorems of Hille–Yosida and Lumer–Phillips that give conditions for a linear operator to generate a semigroup. He then presents a mixture of applications and further developments of the theory. This includes a description of how semigroups are used to solve parabolic partial differential equations, applications to Levy and Feller–Markov processes, Koopmanism in relation to dynamical systems, quantum dynamical semigroups, and applications to generalisations of the Riemann–Liouville fractional integral. Along the way the reader encounters several important ideas in modern analysis including Sobolev spaces, pseudo-differential operators and the Nash i

The theory of semigroups of operators is one of the most important themes in modern analysis. Not only does it have great intellectual beauty, but also wide-ranging applications. In this book the author first presents the essential elements of the theory, introducing the notions of semigroup, generator and resolvent, and establishes the key theorems of Hille–Yosida and Lumer–Phillips that give conditions for a linear operator to generate a semigroup. He then presents a mixture of applications and further developments of the theory. This includes a description of how semigroups are used to solve parabolic partial differential equations, applications to Levy and Feller–Markov processes, Koopmanism in relation to dynamical systems, quantum dynamical semigroups, and applications to generalisations of the Riemann–Liouville fractional integral. Along the way the reader encounters several important ideas in modern analysis including Sobolev spaces, pseudo-differential operators and the Nash i

Avoid data blunders and create truly useful visualizations Avoiding Data Pitfalls is a reputation-saving handbook for those who work with data, designed to help you avoid the all-too-common blunders t

Evaluation for Health Policy and Health Care: A Contemporary Data-Driven Approach explores the best practices and applications for producing, synthesizing, visualizing, using, and disseminating health

Despite advancements in and availability of corpus software in language classrooms facilitating data-driven learning (DDL), the use of such methods with pre-tertiary learners remains rare. This book s

A clear introduction to lexical-functional grammar (LFG), this outstanding textbook sets out a formal approach to the study of language using a step-by-step approach and rich language data. Data from English and a range of other languages is used to illustrate the main concepts, allowing those students not accustomed to working with cross-linguistic data to familiarize themselves with the theory, while also enabling those interested in how the theory can account for more challenging data sets to extend their learning. Exercises ranging from simple technical questions to analyses of a data set, as well as a further resources section with a literature review complete each chapter. The book aims to equip readers with the skills to analyze new data sets and to begin to engage with the primary LFG literature.

A clear introduction to lexical-functional grammar (LFG), this outstanding textbook sets out a formal approach to the study of language using a step-by-step approach and rich language data. Data from English and a range of other languages is used to illustrate the main concepts, allowing those students not accustomed to working with cross-linguistic data to familiarize themselves with the theory, while also enabling those interested in how the theory can account for more challenging data sets to extend their learning. Exercises ranging from simple technical questions to analyses of a data set, as well as a further resources section with a literature review complete each chapter. The book aims to equip readers with the skills to analyze new data sets and to begin to engage with the primary LFG literature.

Written by the leading experts in the field, this text provides systematic coverage of the theory, physics, functional designs, and engineering applications of advanced engineered electromagnetic surfaces. All the essential topics are included, from the fundamental theorems of surface electromagnetics, to analytical models, general sheet transmission conditions (GSTC), metasurface synthesis, and quasi-periodic analysis. A plethora of examples throughout illustrate the practical applications of surface electromagnetics, including gap waveguides, modulated metasurface antennas, transmit arrays, microwave imaging, cloaking, and orbital angular momentum (OAM ) beam generation, allowing readers to develop their own surface electromagnetics-based devices and systems. Enabling a fully comprehensive understanding of surface electromagnetics, this is an invaluable text for researchers, practising engineers and students working in electromagnetics antennas, metasurfaces and optics.

Touch screen panels (TSPs) have become an integral part of modern-day lifestyle. To enhance user experience, attributes such as form-factor flexibility, multi-dimensional sensing, low power consumption and low cost have become highly desirable. This Element addresses the design of multi-functional TSPs with integrated concurrent capture of ubiquitous capacitive touch signals and force information. It compares and contrasts interactive technologies and presents design considerations for multi-dimensional touch screens with high detection sensitivity, accuracy and resolution.

Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its s

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. W

Apply cloud native patterns and practices to deliver responsive, resilient, elastic, and message-driven systems with confidenceKey FeaturesDiscover best practices for applying cloud native patterns to

A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an expone