Inference for Functional Data With Applications

This short book provides an update on various methods for incorporating phase changing materials (PCMs) into building structures. It discusses previous research into optimizing the integration of PCMs

Focusing on the exploration of data with visual methods, Displaying Time Series, Spatial, and Space-Time Data with R, Second Edition, presents methods and R code for producing high-quality static grap

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well

This book focuses on clinical trial design and monitoring with time-to-event endpoints. Detail of subjects of the book are included in book contents. This book not only provides a comprehensive review

Interacting with graphs using queries has emerged as an important research problem for real-world applications that center on large graph data. Given the syntactic complexity of graph query languages

Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come ali

Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come ali

This introduction to automorphic forms on adelic groups G(A) emphasises the role of representation theory. The exposition is driven by examples, and collects and extends many results scattered throughout the literature, in particular the Langlands constant term formula for Eisenstein series on G(A) as well as the Casselman–Shalika formula for the p-adic spherical Whittaker function. This book also covers more advanced topics such as spherical Hecke algebras and automorphic L-functions. Many of these mathematical results have natural interpretations in string theory, and so some basic concepts of string theory are introduced with an emphasis on connections with automorphic forms. Throughout the book special attention is paid to small automorphic representations, which are of particular importance in string theory but are also of independent mathematical interest. Numerous open questions and conjectures, partially motivated by physics, are included to prompt the reader's own research.

Introduction to Mechanism Design: with Computer Applications provides an updated approach to undergraduate Mechanism Design and Kinematics courses/modules for engineering students. The use of web-base

This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods,

This book provides readers with a compelling case for the inclusion of contextual therapy in comprehensive healthcare settings by presenting its applications to individual and family health across the

This book provides readers with a compelling case for the inclusion of contextual therapy in comprehensive healthcare settings by presenting its applications to individual and family health across the

This book deals with problems related to the evaluation of customer satisfaction in very different contexts and ways. Often satisfaction about a product or service is investigated through suitable sur

Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. A large number of reservoir engineering problems associated with geological storage of CO2 require developme

The treatment of a patient with radiation therapy is planned to find the optimal way to treat a tumor while minimizing the dose received by the surrounding normal tissues. In order to better exploit t

Build powerful back-end business logic and complex Enterprise JavaBeans (EJB)-based applications using Java EE 8, Eclipse Enterprise for Java (EE4J), Web Tools Project (WTP), and the Microprofile plat

This new edition provides a state-of-the-art survey of ellipsometric methods used to study organic films and surfaces, from laboratory to synchrotron applications, with a special focus on in-situ use

When you buy a home, should that also mean you have to inform the whole world where you live, how much you paid for it, and whether you financed the purchase with a mortgage loan? In essence, the Neth

This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary c

Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to compl

With the growing popularity of “big data”, the potential value of personal data has attracted more and more attention. Applications built on personal data can create tremendous social and economic ben

This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of

Covers multivariable calculus, starting from the basics and leading up to the three theorems of Green, Gauss, and Stokes, but always with an eye on practical applications. Written for a wide spectrum

Presenting in depth discussions of various statistical models and methods needed for the analysis of medical, biological and biostatistics data, this book emphasizes the analysis of data when normal d

This book introduces readers to copula-based statistical methods for analyzing survival data involving dependent censoring. Primarily focusing on likelihood-based methods performed under copula models

"This book brings a broad spectrum of artificial intelligence and its applications under the purview of multimedia information processing so that it is able to trigger further inspiration among variou

Don't let a fear of numbers hold you back.Today's business environment brings with it an onslaught of data, but leaving the analysis to others in your company just won't cut it. Now more than ever, ma

Kaplan's LSAT PrepTests 52-61 Unlocked features comprehensive explanations for every question in the LSAC's official 10 New Actual, Official LSAT PrepTests with Comparative Reading. Reviewing

A new, full-color, completely updated edition of the key practical guide to chemometrics This new edition of this practical guide on chemometrics, emphasizes the principles and applications behind the

Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets.The data science technology stack d

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional ac

Edited by two of the leading experts in the field, this book provides a comprehensive reference book on feature engineering. The book will provide a description of problems/applications/dataset types

For courses in computer science and programming Starting Out with Java: From Control Structures through Data Structures provides a smooth introduction to programming with Java that moves fl

This book rests upon a smooth integration between image fusion and data mining for information retrieval and content-based mapping in the context of different environmental applications, and it focuse

NOTE: Before purchasing, check with your instructor to ensure you select the correct ISBN. Several versions of the MyLab™ and Mastering™ platforms exist for each title, and registrations a

Do you want more practice with research methods and statistics outside of class?Then the Student Study Guide With IBM® SPSS® Workbook for Research Methods, Statistics, and Applications, Second

Praise for the First Edition:“DNP students may struggle with data management, since their projects are not research, but quality improvement, and this book covers the subject well. I recommend it for

Data Stewardship for Open Science: Implementing FAIR Principles has been written with the intention of making scientists, funders, and innovators in all disciplines and stages of their professional ac