Download or read book Introduction to the Theory of Coverage Processes written by Peter Hall and published by . This book was released on 1988-11-10 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawing on methodology from several areas of probability theory and mathematics, this monograph develops the mathematical theory of models for random coverage patterns, introduces the concepts underlying their generation and illustrates their applications for a variety of fields.
Download or read book An Introduction to the Theory of Point Processes written by D.J. Daley and published by Springer Science & Business Media. This book was released on 2006-04-10 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: Point processes and random measures find wide applicability in telecommunications, earthquakes, image analysis, spatial point patterns, and stereology, to name but a few areas. The authors have made a major reshaping of their work in their first edition of 1988 and now present their Introduction to the Theory of Point Processes in two volumes with sub-titles Elementary Theory and Models and General Theory and Structure. Volume One contains the introductory chapters from the first edition, together with an informal treatment of some of the later material intended to make it more accessible to readers primarily interested in models and applications. The main new material in this volume relates to marked point processes and to processes evolving in time, where the conditional intensity methodology provides a basis for model building, inference, and prediction. There are abundant examples whose purpose is both didactic and to illustrate further applications of the ideas and models that are the main substance of the text.
Download or read book An Introduction to Probability and Stochastic Processes written by James L. Melsa and published by Courier Corporation. This book was released on 2013-01-01 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detailed coverage of probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.
Download or read book Numerical Methods for Stochastic Processes written by Nicolas Bouleau and published by John Wiley & Sons. This book was released on 1994-01-14 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gives greater rigor to numerical treatments of stochastic models. Contains Monte Carlo and quasi-Monte Carlo techniques, simulation of major stochastic procedures, deterministic methods adapted to Markovian problems and special problems related to stochastic integral and differential equations. Simulation methods are given throughout the text as well as numerous exercises.
Download or read book Introduction to Probability written by David F. Anderson and published by Cambridge University Press. This book was released on 2017-11-02 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.
Download or read book Stochastic Processes for Insurance and Finance written by Tomasz Rolski and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Processes for Insurance and Finance offers a thorough yet accessible reference for researchers and practitioners of insurance mathematics. Building on recent and rapid developments in applied probability, the authors describe in general terms models based on Markov processes, martingales and various types of point processes. Discussing frequently asked insurance questions, the authors present a coherent overview of the subject and specifically address: The principal concepts from insurance and finance Practical examples with real life data Numerical and algorithmic procedures essential for modern insurance practices Assuming competence in probability calculus, this book will provide a fairly rigorous treatment of insurance risk theory recommended for researchers and students interested in applied probability as well as practitioners of actuarial sciences. Wiley Series in Probability and Statistics
Download or read book Introduction to Probability Theory and Stochastic Processes written by John Chiasson and published by Wiley. This book was released on 2013-03-29 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique approach to stochastic processes that connects the mathematical formulation of random processes to their use in applications This book presents an innovative approach to teaching probability theory and stochastic processes based on the binary expansion of the unit interval. Departing from standard pedagogy, it uses the binary expansion of the unit interval to explicitly construct an infinite sequence of independent random variables (of any given distribution) on a single probability space. This construction then provides the framework to understand the mathematical formulation of probability theory for its use in applications. Features include: The theory is presented first for countable sample spaces (Chapters 1-3) and then for uncountable sample spaces (Chapters 4-18) Coverage of the explicit construction of i.i.d. random variables on a single probability space to explain why it is the distribution function rather than the functional form of random variables that matters when it comes to modeling random phenomena Explicit construction of continuous random variables to facilitate the "digestion" of random variables, i.e., how they are used in contrast to how they are defined Explicit construction of continuous random variables to facilitate the two views of expectation: as integration over the underlying probability space (abstract view) or as integration using the density function (usual view) A discussion of the connections between Bernoulli, geometric, and Poisson processes Incorporation of the Johnson-Nyquist noise model and an explanation of why (and when) it is valid to use a delta function to model its autocovariance Comprehensive, astute, and practical, Introduction to Probability Theory and Stochastic Processes is a clear presentation of essential topics for those studying communications, control, machine learning, digital signal processing, computer networks, pattern recognition, image processing, and coding theory.
Download or read book Stochastic Processes written by Robert G. Gallager and published by Cambridge University Press. This book was released on 2013-12-12 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive textbook on stochastic processes, written by one of the world's leading information theorists, covering both theory and applications.
Download or read book Biostatistical Methods written by John M. Lachin and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive coverage of classical and modern methods of biostatistics Biostatistical Methods focuses on the assessment of risks and relative risks on the basis of clinical investigations. It develops basic concepts and derives biostatistical methods through both the application of classical mathematical statistical tools and more modern likelihood-based theories. The first half of the book presents methods for the analysis of single and multiple 2x2 tables for cross-sectional, prospective, and retrospective (case-control) sampling, with and without matching using fixed and two-stage random effects models. The text then moves on to present a more modern likelihood- or model-based approach, which includes unconditional and conditional logistic regression; the analysis of count data and the Poisson regression model; and the analysis of event time data, including the proportional hazards and multiplicative intensity models. The book contains a technical appendix that presents the core mathematical statistical theory used for the development of classical and modern statistical methods. Biostatistical Methods: The Assessment of Relative Risks: * Presents modern biostatistical methods that are generalizations of the classical methods discussed * Emphasizes derivations, not just cookbook methods * Provides copious reference citations for further reading * Includes extensive problem sets * Employs case studies to illustrate application of methods * Illustrates all methods using the Statistical Analysis System(r) (SAS) Supplemented with numerous graphs, charts, and tables as well as a Web site for larger data sets and exercises, Biostatistical Methods: The Assessment of Relative Risks is an excellent guide for graduate-level students in biostatistics and an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.
Download or read book Finite Mixture Models written by Geoffrey McLachlan and published by John Wiley & Sons. This book was released on 2004-03-22 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, comprehensive account of major issues in finitemixture modeling This volume provides an up-to-date account of the theory andapplications of modeling via finite mixture distributions. With anemphasis on the applications of mixture models in both mainstreamanalysis and other areas such as unsupervised pattern recognition,speech recognition, and medical imaging, the book describes theformulations of the finite mixture approach, details itsmethodology, discusses aspects of its implementation, andillustrates its application in many common statisticalcontexts. Major issues discussed in this book include identifiabilityproblems, actual fitting of finite mixtures through use of the EMalgorithm, properties of the maximum likelihood estimators soobtained, assessment of the number of components to be used in themixture, and the applicability of asymptotic theory in providing abasis for the solutions to some of these problems. The author alsoconsiders how the EM algorithm can be scaled to handle the fittingof mixture models to very large databases, as in data miningapplications. This comprehensive, practical guide: * Provides more than 800 references-40% published since 1995 * Includes an appendix listing available mixture software * Links statistical literature with machine learning and patternrecognition literature * Contains more than 100 helpful graphs, charts, and tables Finite Mixture Models is an important resource for both applied andtheoretical statisticians as well as for researchers in the manyareas in which finite mixture models can be used to analyze data.
Download or read book Reliability written by Wallace R. Blischke and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing together business and engineering to reliability analysisWith manufactured products exploding in numbers and complexity,reliability studies play an increasingly critical role throughout aproduct's entire life cycle-from design to post-sale support.Reliability: Modeling, Prediction, and Optimization presents aremarkably broad framework for the analysis of the technical andcommercial aspects of product reliability, integrating concepts andmethodologies from such diverse areas as engineering, materialsscience, statistics, probability, operations research, andmanagement. Written in plain language by two highly respectedexperts in the field, this practical work provides engineers,operations managers, and applied statisticians with bothqualitative and quantitative tools for solving a variety ofcomplex, real-world reliability problems. A wealth of examples andcase studies accompanies: * Comprehensive coverage of assessment, prediction, and improvementat each stage of a product's life cycle * Clear explanations of modeling and analysis for hardware rangingfrom a single part to whole systems * Thorough coverage of test design and statistical analysis ofreliability data * A special chapter on software reliability * Coverage of effective management of reliability, product support,testing, pricing, and related topics * Lists of sources for technical information, data, and computerprograms * Hundreds of graphs, charts, and tables, as well as over 500references * PowerPoint slides are available from the Wiley editorialdepartment.
Download or read book A Course in Time Series Analysis written by Daniel Peña and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time series Shared balance between theory and application Exercise series sets Many real data examples Consistent style and clear, common notation in all contributions 60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.
Download or read book Mathematics of Chance written by Jirí Andel and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Chance utilizes simple, real-world problems-some of which have only recently been solved-to explain fundamental probability theorems, methods, and statistical reasoning. Jiri Andel begins with a basic introduction to probability theory and its important points before moving on to more specific sections on vital aspects of probability, using both classic and modern problems. Each chapter begins with easy, realistic examples before covering the general formulations and mathematical treatments used. The reader will find ample use for a chapter devoted to matrix games and problem sets concerning waiting, probability calculations, expectation calculations, and statistical methods. A special chapter utilizes problems that relate to areas of mathematics outside of statistics and considers certain mathematical concepts from a probabilistic point of view. Sections and problems cover topics including: * Random walks * Principle of reflection * Probabilistic aspects of records * Geometric distribution * Optimization * The LAD method, and more Knowledge of the basic elements of calculus will be sufficient in understanding most of the material presented here, and little knowledge of pure statistics is required. Jiri Andel has produced a compact reference for applied statisticians working in industry and the social and technical sciences, and a book that suits the needs of students seeking a fundamental understanding of probability theory.
Download or read book Comparative Statistical Inference written by Vic Barnett and published by John Wiley & Sons. This book was released on 1999-08-03 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fully updated and revised third edition, presents a wide ranging, balanced account of the fundamental issues across the full spectrum of inference and decision-making. Much has happened in this field since the second edition was published: for example, Bayesian inferential procedures have not only gained acceptance but are often the preferred methodology. This book will be welcomed by both the student and practising statistician wishing to study at a fairly elementary level, the basic conceptual and interpretative distinctions between the different approaches, how they interrelate, what assumptions they are based on, and the practical implications of such distinctions. As in earlier editions, the material is set in a historical context to more powerfully illustrate the ideas and concepts. Includes fully updated and revised material from the successful second edition Recent changes in emphasis, principle and methodology are carefully explained and evaluated Discusses all recent major developments Particular attention is given to the nature and importance of basic concepts (probability, utility, likelihood etc) Includes extensive references and bibliography Written by a well-known and respected author, the essence of this successful book remains unchanged providing the reader with a thorough explanation of the many approaches to inference and decision making.
Download or read book Bootstrap Methods written by Michael R. Chernick and published by John Wiley & Sons. This book was released on 2011-09-23 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical and accessible introduction to the bootstrap method——newly revised and updated Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics. Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features: The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data New examples and illustrations as well as extensive historical notes at the end of each chapter With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.
Download or read book Nonresponse in Household Interview Surveys written by Robert M. Groves and published by John Wiley & Sons. This book was released on 2012-08-29 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive framework for both reduction of nonresponse andpostsurvey adjustment for nonresponse This book provides guidance and support for survey statisticianswho need to develop models for postsurvey adjustment fornonresponse, and for survey designers and practitioners attemptingto reduce unit nonresponse in household interview surveys. Itpresents the results of an eight-year research program that hasassembled an unprecedented data set on respondents andnonrespondents from several major household surveys in the UnitedStates. Within a comprehensive conceptual framework of influences onnonresponse, the authors investigate every aspect of surveycooperation, from the influences of household characteristics andsocial and environmental factors to the interaction betweeninterviewers and householders and the design of the surveyitself. Nonresponse in Household Interview Surveys: * Provides a theoretical framework for understanding and studyinghousehold survey nonresponse * Empirically explores the individual and combined influences ofseveral factors on nonresponse * Presents chapter introductions, summaries, and discussions onpractical implications to clarify concepts and theories * Supplies extensive references for further study and inquiry Nonresponse in Household Interview Surveys is an important resourcefor professionals and students in survey methodology/researchmethods as well as those who use survey methods or data inbusiness, government, and academia. It addresses issues critical todealing with nonresponse in surveys, reducing nonresponse duringsurvey data collection, and constructing statistical compensationsfor the effects of nonresponse on key survey estimates.
Download or read book Foundations of Time Series Analysis and Prediction Theory written by Mohsen Pourahmadi and published by John Wiley & Sons. This book was released on 2001-06-01 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of time series for researchers and students This volume provides a mathematical foundation for time seriesanalysis and prediction theory using the idea of regression and thegeometry of Hilbert spaces. It presents an overview of the tools oftime series data analysis, a detailed structural analysis ofstationary processes through various reparameterizations employingtechniques from prediction theory, digital signal processing, andlinear algebra. The author emphasizes the foundation and structureof time series and backs up this coverage with theory andapplication. End-of-chapter exercises provide reinforcement for self-study andappendices covering multivariate distributions and Bayesianforecasting add useful reference material. Further coveragefeatures: * Similarities between time series analysis and longitudinal dataanalysis * Parsimonious modeling of covariance matrices through ARMA-likemodels * Fundamental roles of the Wold decomposition andorthogonalization * Applications in digital signal processing and Kalmanfiltering * Review of functional and harmonic analysis and predictiontheory Foundations of Time Series Analysis and Prediction Theory guidesreaders from the very applied principles of time series analysisthrough the most theoretical underpinnings of prediction theory. Itprovides a firm foundation for a widely applicable subject forstudents, researchers, and professionals in diverse scientificfields.
