chapman and hall crc jun 2021 (27 risultati)

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Are you buying a car or smartphone or dishwasher We bet long-term, trouble-free operation (i.e., high reliability) is among the top three things you look for. Reliability problems can lead to everything from minor inconveniences to human disasters. Ensuring high reliability in designing and building manufactured products is principally an engineering challenge-but statistics plays a key role. Achieving Product Reliability explains in a non-technical manner how statistics is used in modern product reliability assurance.Features:Describes applications of statistics in reliability assurance in design, development, validation, manufacturing, and field tracking.Uses real-life examples to illustrate key statistical concepts such as the Weibull and lognormal distributions, hazard rate, and censored data. Demonstrates the use of graphical tools in such areas as accelerated testing, degradation data modeling, and repairable systems data analysis.Presents opportunities for profitably applying statistics in the era of Big Data and Industrial Internet of Things (IIoT) utilizing, for example, the instantaneous transmission of large quantities of field data.Whether you are an intellectually curious citizen, student, manager, budding reliability professional, or academician seeking practical applications, Achieving Product Reliability is a great starting point for a big-picture view of statistics in reliability assurance.The authors are world-renowned experts on this topic with extensive experience as company-wide statistical resources for a global conglomerate, consultants to business and government, and researchers of statistical methods for reliability applications. 250 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Geometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations as a Euclidean cloud of points. Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to clouds of points that make no assumption on the process of generating data or distributions, and that are not based on random modelling but on permutation procedures recasting in a combinatorial framework. It focuses particularly on the comparison of a group of observations to a reference population (combinatorial test) or to a reference value of a location parameter (geometric test), and on problems of homogeneity, that is the comparison of several groups for two basic designs. These methods involve the use of combinatorial procedures to build a reference set in which we place the data. The chosen test statistics lead to original extensions, such as the geometric interpretation of the observed level, and the construction of a compatibility region.Features:Defines precisely the object under study in the context of multidimensional procedures, that is clouds of pointsPresents combinatorial tests and related computations with R and Coheris SPAD software Includes four original case studies to illustrate application of the tests Includes necessary mathematical background to ensure it is self-containedThis book is suitable for researchers and students of multivariate statistics, as well as applied researchers of various scientific disciplines. It could be used for a specialized course taught at either master or PhD level. 270 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 activities broadly aware of the need, complexity, and challenges associated with open science, modern science communication, and data stewardship. The FAIR principles are used as a guide throughout the text, and this book should leave experimentalists consciously incompetent about data stewardship and motivated to respect data stewards as representatives of a new profession, while possibly motivating others to consider a career in the field.The Elektronisches Buch, avalable for no additional cost when you buy the paperback, will be updated every 6 months on average (providing that significant updates are needed or avaialble). Readers will have the opportunity to contribute material towards these updates, and to develop their own data management plans, via the free Data Stewardship Wizard. 246 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information from individuals who have experienced the event of interest, and automatically controls for multiplicative time-invariant confounders, even when these are unmeasured or unknown. It is increasingly being used in epidemiology, most frequently to study the safety of vaccines and pharmaceutical drugs.Key features of the book include:A thorough yet accessible description of the SCCS method, with mathematical details provided in separate starred sections.Comprehensive discussion of assumptions and how they may be verified.A detailed account of different SCCS models, extensions of the SCCS method, and the design of SCCS studies.Extensive practical illustrations and worked examples from epidemiology.Full computer code from the associated R package SCCS, which includes all the data sets used in the book.The book is aimed at a broad range of readers, including epidemiologists and medical statisticians who wish to use the SCCS method, and also researchers with an interest in statistical methodology. The three authors have been closely involved with the inception, development, popularisation and programming of the SCCS method. 378 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness, (ii) computational illustration and implementation, and (iii) conciseness and accessibility to upper-level undergraduate and M.S. students. Basic theoretical results are presented in a mathematically convincing way, and the methods of data analysis are developed through examples and exercises parsed in R. A student with a basic course in mathematical statistics will learn both how to analyze time series and how to interpret the results.The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth, as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling. The second half of the book focuses on statistical inference, the fitting of time series models, as well as computational facets of forecasting. Many time series of interest are nonlinear in which case classical inference methods can fail, but bootstrap methods may come to the rescue. Distinctive features of the book are the emphasis on geometric notions and the frequency domain, the discussion of entropy maximization, and a thorough treatment of recent computer-intensive methods for time series such as subsampling and the bootstrap. There are more than 600 exercises, half of which involve R coding and/or data analysis. Supplements include a website with 12 key data sets and all R code for the book's examples, as well as the solutions to exercises. 588 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Google's Programmable Search Engines (PSEs, previously called Custom Search Engines) provide search opportunities that are unavailable with any other tool. PSEs have advanced settings and search operators that are not supported by 'regular' Google. With PSEs, it is possible to perform filtered searches within parts of the web as if they were databases!While lots of professionals use existing PSEs to source for talent or with other research goals, few people have experience creating them. Even fewer know about powerful PSE-only search operators. The main reason PSEs are not as popular as they should be is that it is not easy to get educated on PSE creation. There is little information online and no books (other than this one) on the subject. Even less info is available on the 'structured' operators that allow for filtered searches.The first of its kind, this book hopes to popularize these fun and powerful tools so that many more people can include PSEs in their work.Key Features:A detailed introduction tocreating PSEs, including info absent in Google's helpA 'hack' for creating PSEs that look for profiles in secondsAn introduction to advanced PSE-only search operators allowed to perform filtered searches of parts of the webA 'hack' for expanding Google's search limits to 500 termsUse cases, examples, and approaches that would be educational for those doing online researchThis bookwill be of interest toresearchers, OSINT specialists, investigative journalists, Competitive Intelligence people, recruiters, and Sourcers, to name a few categories, and to the general public interested in how to search better. 196 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students.FeaturesProvides an overview of the methods and applications of pattern recognition of time seriesCovers a wide range of techniques, including unsupervised and supervised approachesIncludes a range of real examples from medicine, finance, environmental science, and moreR and MATLAB code, and relevant data sets are available on a supplementary website 246 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A Sound Basis for the Theory of Statistical InferenceMeasuring Statistical Evidence Using Relative Belief provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It shows that being explicit about how to measure statistical evidence allows you to answer the basic question of when a statistical analysis is correct.The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application. 252 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Despite the unobserved components model (UCM) having many advantages over more popular forecasting techniques based on regression analysis, exponential smoothing, and ARIMA, the UCM is not well known among practitioners outside the academic community. Time Series Modelling with Unobserved Components rectifies this deficiency by giving a practical overview of the UCM approach, covering some theoretical details, several applications, and the software for implementing UCMs.The book's first part discusses introductory time series and prediction theory. Unlike most other books on time series, this text includes a chapter on prediction at the beginning because the problem of predicting is not limited to the field of time series analysis.The second part introduces the UCM, the state space form, and related algorithms. It also provides practical modeling strategies to build and select the UCM that best fits the needs of time series analysts.The third part presents real-world applications, with a chapter focusing on business cycle analysis and the construction of band-pass filters using UCMs. The book also reviews software packages that offer ready-to-use procedures for UCMs as well as systems popular among statisticians and econometricians that allow general estimation of models in state space form.This book demonstrates the numerous benefits of using UCMs to model time series data. UCMs are simple to specify, their results are easy to visualize and communicate to non-specialists, and their forecasting performance is competitive. Moreover, various types of outliers can easily be identified, missing values are effortlessly managed, and working contemporaneously with time series observed at different frequencies poses no problem. 276 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues.The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers. 210 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations.Focuses on the recent subfield of decision analysis, ARA Compares ideas from decision theory and game theoryUses multi-agent influence diagrams (MAIDs) throughout to help readers visualize complex information structuresApplies the ARA approach to simultaneous games, auctions, sequential games, and defend-attack gamesContains an extended case study based on a real application in railway security, which provides a blueprint for how to perform ARA in similar security situations Includes exercises at the end of most chapters, with selected solutions at the back of the bookThe book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponent's goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on all unknown quantities. This produces a distribution over the actions of the opponent and enables analysts to maximize their expected utilities. 226 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice. This monograph provides a comprehensive account of asymptotic analysis of mixed effects models. The monograph is suitable for researchers and graduate students who wish to learn about asymptotic tools and research problems in mixed effects models. It may also be used as a reference book for a graduate-level course on mixed effects models, or asymptotic analysis. 274 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysis of selected experimental data in toxicology and presents assay-specific suggestions, such as for the in vitro micronucleus assay. Mostly focusing on hypothesis testing, the book covers standardized bioassays for chemicals, drugs, and environmental pollutants. It is organized according to selected toxicological assays, including: Short-term repeated toxicity studiesLong-term carcinogenicity assays Studies on reproductive toxicity Mutagenicity assays Toxicokinetic studies The book also discusses proof of safety (particularly in ecotoxicological assays), toxicogenomics, the analysis of interlaboratory studies and the modeling of dose-response relationships for risk assessment. For each toxicological problem, the author describes the statistics involved, matching data example, R code, and outcomes and their interpretation. This approach allows you to select a certain bioassay, identify the specific data structure, run the R code with the data example, understand the test outcome and interpretation, and replace the data set with your own data and run again. 254 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential. 214 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -If you know a little bit about financial mathematics but don't yet know a lot about programming, then C++ for Financial Mathematics is for you.C++ is an essential skill for many jobs in quantitative finance, but learning it can be a daunting prospect. This book gathers together everything you need to know to price derivatives in C++ without unnecessary complexities or technicalities. It leads the reader step-by-step from programming novice to writing a sophisticated and flexible financial mathematics library. At every step, each new idea is motivated and illustrated with concrete financial examples.As employers understand, there is more to programming than knowing a computer language. As well as covering the core language features of C++, this book teaches the skills needed to write truly high quality software. These include topics such as unit tests, debugging, design patterns and data structures. The book teaches everything you need to know to solve realistic financial problems in C++. It can be used for self-study or as a textbook for an advanced undergraduate or master's level course. 412 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical basis of the methodology, new developments in variable selection and multiple testing, and new examples and applications. It includes an R package for all the methods and examples that supplement the book. 468 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 226 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features:Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization. 436 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Achieve Technological Advancements in Applied Science and Engineering Using Efficient Experiments That Consume the Least Amount of ResourcesWritten by longtime experimental design guru Thomas B. Barker and experimental development/Six Sigma expert Andrew Milivojevich, Quality by Experimental Design, Fourth Edition shows how to design and analyze experiments statistically, drive process and product innovation, and improve productivity. The book presents an approach to experimentation that assesses many factors, builds predictive models, and verifies the models.New to the Fourth EditionUpdated computer programs used to perform simulations, including the latest version of Minitab® Four new chapters on mixture experiments: Introduction to Mixture Experiments, The Simplex Lattice Design, The Simplex Centroid Design, and Constrained MixturesAdditional exercises and Minitab updatesA Proven, Practical Guide for Newcomers and Seasoned Practitioners in Engineering, Applied Science, Quality, and Six Sigma This bestselling, applied text continues to cover a broad range of experimental designs for practical use in applied research, quality and process engineering, and product development. With its easy-to-read, conversational style, the book is suitable for any course in applied statistical experimental design or in a Six Sigma program. 754 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book illustrates how MAPLE(TM) can be used to supplement a standard, elementary text in ordinary and partial differential equation. The authors are firm believers in the teaching of mathematics as an experimental science where the student does numerous calculations and then synthesizes these experiments into a general theory. The goal of the book is to teach the students enough about the computer algebra system MAPLE(TM) so that it can be used in an investigative way. This book was developed through ten years of instruction in the differential equations course. 244 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Principles of Copula Theory explores the state of the art on copulas and provides you with the foundation to use copulas in a variety of applications. Throughout the book, historical remarks and further readings highlight active research in the field, including new results, streamlined presentations, and new proofs of old results.After covering the essentials of copula theory, the book addresses the issue of modeling dependence among components of a random vector using copulas. It then presents copulas from the point of view of measure theory, compares methods for the approximation of copulas, and discusses the Markov product for 2-copulas. The authors also examine selected families of copulas that possess appealing features from both theoretical and applied viewpoints. The book concludes with in-depth discussions on two generalizations of copulas: quasi- and semi-copulas.Although copulas are not the solution to all stochastic problems, they are an indispensable tool for understanding several problems about stochastic dependence. This book gives you the solid and formal mathematical background to apply copulas to a range of mathematical areas, such as probability, real analysis, measure theory, and algebraic structures. 332 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Capture-recapture methods have been used in biology and ecology for more than 100 years. However, it is only recently that these methods have become popular in the social and medical sciences to estimate the size of elusive populations such as illegal immigrants, illicit drug users, or people with a drinking problem. Capture-Recapture Methods for the Social and Medical Sciences brings together important developments which allow the application of these methods. It has contributions from more than 40 researchers, and is divided into eight parts, including topics such as ratio regression models, capture-recapture meta-analysis, extensions of single and multiple source models, latent variable models and Bayesian approaches. The book is suitable for everyone who is interested in applying capture-recapture methods in the social and medical sciences. Furthermore, it is also of interest to those working with capture-recapture methods in biology and ecology, as there are some important developments covered in the book that also apply to these classical application areas. 464 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book 'Flexible Regression and Smoothing: Using GAMLSS in R', [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application.Key features:Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions.Comprehensive summary tables of the properties of the distributions.Discusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness.Includes mixed distributions which are continuous distributions with additional specific values with point probabilities.Includes many real data examples, with R code integrated in the text for ease of understanding and replication.Supplemented by the gamlss website.This book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions. 590 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A First Step toward a Unified Theory of Richly Parameterized Linear ModelsUsing mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based understanding of models with random effects.Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. The author examines what is known and unknown about mixed linear models and identifies research opportunities.The first two parts of the book cover an existing syntax for unifying models with random effects. The text explains how richly parameterized models can be expressed as mixed linear models and analyzed using conventional and Bayesian methods.In the last two parts, the author discusses oddities that can arise when analyzing data using these models. He presents ways to detect problems and, when possible, shows how to mitigate or avoid them. The book adapts ideas from linear model theory and then goes beyond that theory by examining the information in the data about the mixed linear model's covariance matrices.Each chapter ends with two sets of exercises. Conventional problems encourage readers to practice with the algebraic methods and open questions motivate readers to research further. Supporting materials, including datasets for most of the examples analyzed, are available on the author's website. 470 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -How can major corporations and governments more quickly and accurately detect and address cyberattacks on their networks How can local authorities improve early detection and prevention of epidemics How can researchers improve the identification and classification of space objects in difficult (e.g., dim) settings These questions, among others in dozens of fields, can be addressed using statistical methods of sequential hypothesis testing and changepoint detection. This book considers sequential changepoint detection for very general non-i.i.d. stochastic models, that is, when the observed data is dependent and non-identically distributed. Previous work has primarily focused on changepoint detection with simple hypotheses and single-stream data. This bookextends the asymptotic theory of change detection to the case of composite hypotheses as well as for multi-stream data when the number of affected streams is unknown. These extensions are more relevant for practical applications, including in modern, complex information systems and networks. These extensions are illustratedusing Markov, hidden Markov, state-space, regression, and autoregression models, and several applications, including near-Earth space informatics and cybersecurity are discussed. This book is aimed at graduate students and researchers in statistics and applied probability who are familiar with complete convergence, Markov random walks, renewal and nonlinear renewal theories, Markov renewal theory, and uniform ergodicity of Markov processes. Key features:Design and optimality properties of sequential hypothesis testing and change detection algorithms (in Bayesian, minimax, pointwise, and other settings)Consideration of very general non-i.i.d. stochastic models that include Markov, hidden Markov, state-space linear and non-linear models, regression, and autoregression modelsMultiple decision-making problems, including quickest change detection-identificationReal-world applications to object detection and tracking, near-Earth space informatics, computer network surveillance and security, and other topics 320 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mendelian Randomization: Methods For Causal Inference Using Genetic Variants provides thorough coverage of the methods and practical elements of Mendelian randomization analysis. It brings together diverse aspects of Mendelian randomization from the fields of epidemiology, statistics, genetics, and bioinformatics.Through multiple examples, the first part of the book introduces the reader to the concept of Mendelian randomization, showing how to perform simple Mendelian randomization investigations and interpret the results. The second part of the book addresses specific methodological issues relevant to the practice of Mendelian randomization, including robust methods, weak instruments, multivariable methods, and power calculations. The authors present the theoretical aspects of these issues in an easy-to-understand way by using non-technical language. The last part of the book examines the potential for Mendelian randomization in the future, exploring both methodological and applied developments.FeaturesOffers first-hand, in-depth guidance on Mendelian randomization from leaders in the fieldMakes the diverse aspects of Mendelian randomization understandable to newcomersIllustrates technical details using data from applied analysesDiscusses possible future directions for research involving Mendelian randomizationSoftware code is provided in the relevant chapters and is also available at the supplementary websiteThis book gives epidemiologists, statisticians, geneticists, and bioinformaticians the foundation to understand how to use genetic variants as instrumental variables in observational data.New in Second Edition: The second edition of the book has been substantially re-written to reduce the amount of technical content, and emphasize practical consequences of theoretical issues. Extensive material on the use of two-sample Mendelian randomization and publicly-available summarized data has been added. The book now includes several real-world examples that show how Mendelian randomization can be used to address questions of disease aetiology, target validation, and drug development 240 pp. Englisch.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many experiments have shown the human brain generally has very serious problems dealing with probability and chance. A greater understanding of probability can help develop the intuition necessary to approach risk with the ability to make more informed (and better) decisions. The first four chapters offer the standard content for an introductory probability course, albeit presented in a much different way and order. The chapters afterward include some discussion of different games, different 'ideas' that relate to the law of large numbers, and many more mathematical topics not typically seen in such a book. The use of games is meant to make the book (and course) feel like fun! Since many of the early games discussed are casino games, the study of those games, along with an understanding of the material in later chapters, should remind you that gambling is a bad idea; you should think of placing bets in a casino as paying for entertainment. Winning can, obviously, be a fun reward, but should not ever be expected.Changes for the Second Edition:New chapter on Game TheoryNew chapter on Sports MathematicsThe chapter on Blackjack, which was Chapter 4 in the first edition, appears later in the book. Reorganization has been done to improve the flow of topics and learning.New sections on Arkham Horror, Uno, and Scrabble have been added.Even more exercises were added! The goal for this textbook is to complement the inquiry-based learning movement. In my mind, concepts and ideas will stick with the reader more when they are motivated in an interesting way. Here, we use questions about various games (not just casino games) to motivate the mathematics, and I would say that the writing emphasizes a 'just-in-time' mathematics approach. Topics are presented mathematically as questions about the games themselves are posed.Table of ContentsPreface1. Mathematics and Probability 2. Roulette and Craps: Expected Value 3. Counting: Poker Hands 4. More Dice: Counting and Combinations, and Statistics 5. Game Theory: Poker Bluffing and Other Games 6. Probability/Stochastic Matrices: Board Game Movement 7. Sports Mathematics: Probability Meets Athletics 8. Blackjack: Previous Methods Revisited 9. A Mix of Other Games 10. Betting Systems: Can You Beat the System 11. Potpourri: Assorted Adventures in Probability Appendices Tables Answers and Selected Solutions Bibliography BiographyDr. David G. Taylor is a professor of mathematics and an associate dean for academic affairs at Roanoke College in southwest Virginia. He attended Lebanon Valley College for his B.S. in computer science and mathematics and went to the University of Virginia for his Ph.D. While his graduate school focus was on studying infinite dimensional Lie algebras, he started studying the mathematics of various games in order to have a more undergraduate-friendly research agenda. Work done with two Roanoke College students, Heather Cook and Jonathan Marino, appears in this book! Currently he owns over 100 different board games and enjoys using probability in his decision-making while playing most of those games. In his spare time, he enjoys reading, cooking, coding, playing his board games, and spending time with his six-year-old dog Lilly. 516 pp. Englisch.