markov chains analytic and monte carlo computations wiley series in probability and statistics

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Markov Chains

Author : Carl Graham
ISBN : 9781118517079
Genre : Mathematics
File Size : 44. 80 MB
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Markov Chains: Analytic and Monte Carlo Computations introduces the main notions related to Markov chains and provides explanations on how to characterize, simulate, and recognize them. Starting with basic notions, this book leads progressively to advanced and recent topics in the field, allowing the reader to master the main aspects of the classical theory. This book also features: Numerous exercises with solutions as well as extended case studies. A detailed and rigorous presentation of Markov chains with discrete time and state space. An appendix presenting probabilistic notions that are necessary to the reader, as well as giving more advanced measure-theoretic notions.

Time Series Analysis

Author : Wilfredo Palma
ISBN : 9781118634233
Genre : Mathematics
File Size : 61. 5 MB
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A modern and accessible guide to the analysis of introductory time series data Featuring an organized and self-contained guide, Time Series Analysis provides a broad introduction to the most fundamental methodologies and techniques of time series analysis. The book focuses on the treatment of univariate time series by illustrating a number of well-known models such as ARMA and ARIMA. Providing contemporary coverage, the book features several useful and newlydeveloped techniques such as weak and strong dependence, Bayesian methods, non-Gaussian data, local stationarity, missing values and outliers, and threshold models. Time Series Analysis includes practical applications of time series methods throughout, as well as: Real-world examples and exercise sets that allow readers to practice the presented methods and techniques Numerous detailed analyses of computational aspects related to the implementation of methodologies including algorithm efficiency, arithmetic complexity, and process time End-of-chapter proposed problems and bibliographical notes to deepen readers’ knowledge of the presented material Appendices that contain details on fundamental concepts and select solutions of the problems implemented throughout A companion website with additional data fi les and computer codes Time Series Analysis is an excellent textbook for undergraduate and beginning graduate-level courses in time series as well as a supplement for students in advanced statistics, mathematics, economics, finance, engineering, and physics. The book is also a useful reference for researchers and practitioners in time series analysis, econometrics, and finance. Wilfredo Palma, PhD, is Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. He has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics. He is the author of Long-Memory Time Series: Theory and Methods, also published by Wiley.

Spatial And Spatio Temporal Geostatistical Modeling And Kriging

Author : Gema Fernández-Avilés
ISBN : 9781118413180
Genre : Mathematics
File Size : 86. 49 MB
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Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. The most innovative developments in the different steps of the kriging process. An up-to-date account of strategies for dealing with data evolving in space and time. An accompanying website featuring R code and examples

The Fitness Of Information

Author : Chaomei Chen
ISBN : 9781118594209
Genre : Mathematics
File Size : 82. 47 MB
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Theories and practices to assess critical information in acomplex adaptive system Organized for readers to follow along easily, The Fitness ofInformation: Quantitative Assessments of Critical Evidenceprovides a structured outline of the key challenges in assessingcrucial information in a complex adaptive system. Illustrating avariety of computational and explanatory challenges, the bookdemonstrates principles and practical implications of exploring andassessing the fitness of information in an extensible framework ofadaptive landscapes. The book’s first three chapters introduce fundamentalprinciples and practical examples in connection to the nature ofaesthetics, mental models, and the subjectivity of evidence. Inparticular, the underlying question is how these issues can beaddressed quantitatively, not only computationally but alsoexplanatorily. The next chapter illustrates how one can reduce thelevel of complexity in understanding the structure and dynamics ofscientific knowledge through the design and use of the CiteSpacesystem for visualizing and analyzing emerging trends in scientificliterature. The following two chapters explain the concepts ofstructural variation and the fitness of information in a frameworkthat builds on the idea of fitness landscape originally introducedto study population evolution. The final chapter presents adual-map overlay technique and demonstrates how it supports avariety of analytic tasks for a new type of portfolioanalysis. The Fitness of Information: Quantitative Assessments of CriticalEvidence also features: In-depth case studies and examples that characterizefar-reaching concepts, illustrate underlying principles, anddemonstrate profound challenges and complexities at various levelsof analytic reasoning Wide-ranging topics that underline the common theme, from thesubjectivity of evidence in criminal trials to detecting earlysigns of critical transitions and mechanisms behind radicalpatents An extensible and unifying framework for visual analytics bytransforming analytic reasoning tasks to the assessment of criticalevidence The Fitness of Information: Quantitative Assessments of CriticalEvidence is a suitable reference for researchers, analysts, andpractitioners who are interested in analyzing evidence and makingdecisions with incomplete, uncertain, and even conflictinginformation. The book is also an excellent textbook forupper-undergraduate and graduate-level courses on visual analytics,information visualization, and business analytics and decisionsupport systems.

Multivariate Density Estimation

Author : David W. Scott
ISBN : 9781118575536
Genre : Mathematics
File Size : 47. 42 MB
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Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.

Understanding Computational Bayesian Statistics

Author : William M. Bolstad
ISBN : 9781118209929
Genre : Mathematics
File Size : 51. 98 MB
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A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistical models, including the multiple linear regression model, the hierarchical mean model, the logistic regression model, and the proportional hazards model. The book begins with an outline of the similarities and differences between Bayesian and the likelihood approaches to statistics. Subsequent chapters present key techniques for using computer software to draw Monte Carlo samples from the incompletely known posterior distribution and performing the Bayesian inference calculated from these samples. Topics of coverage include: Direct ways to draw a random sample from the posterior by reshaping a random sample drawn from an easily sampled starting distribution The distributions from the one-dimensional exponential family Markov chains and their long-run behavior The Metropolis-Hastings algorithm Gibbs sampling algorithm and methods for speeding up convergence Markov chain Monte Carlo sampling Using numerous graphs and diagrams, the author emphasizes a step-by-step approach to computational Bayesian statistics. At each step, important aspects of application are detailed, such as how to choose a prior for logistic regression model, the Poisson regression model, and the proportional hazards model. A related Web site houses R functions and Minitab macros for Bayesian analysis and Monte Carlo simulations, and detailed appendices in the book guide readers through the use of these software packages. Understanding Computational Bayesian Statistics is an excellent book for courses on computational statistics at the upper-level undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners who use computer programs to conduct statistical analyses of data and solve problems in their everyday work.

The Mathematica Journal

Author :
ISBN : UOM:35128001707387
Genre : Mathematica (Computer file)
File Size : 32. 33 MB
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Applied Logistic Regression

Author : David W. Hosmer, Jr.
ISBN : 9781118548356
Genre : Mathematics
File Size : 59. 51 MB
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A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.

Encyclopedia Of Statistical Sciences

Author :
ISBN : 0471743755
Genre : Mathematics
File Size : 25. 35 MB
Format : PDF
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With the publication of this update installment, the Encyclopedia of Statistical Sciences retains its position as the only cutting-edge reference of choice for those working in statistics, probability theory, biostatistics, quality control, and economics and in applications of statistical methods in sociology, engineering, computer and communication science, biomedicine, psychology, and many other areas.

Encyclopedia Of Environmetrics

Author : Abdel H. El-Shaarawi
ISBN : 0471899976
Genre : Mathematics
File Size : 58. 34 MB
Format : PDF, ePub
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A comprehensive overview of environmetric research and its applications... Environmetrics covers the development and application of quantitative methods in the environmental sciences. It provides essential tools for understanding, predicting, and controlling the impacts of agents, both man-made and natural, which affect the environment. Basic and applied research in this area covers a broad range of topics. Primary among these are the quantitative sciences, such as statistics, probability and applied mathematics, chemometrics, and econometrics. Applications are also important, for example in, ecology and environmental biology, public health, atmospheric science, geology, engineering, risk management, and regulatory/governmental policy amongst others. * Divided into 12 sections, the Encyclopedia brings together over 600 detailed articles which have been carefully selected and reviewed through the collaborative efforts of the Editors-in-Chief and the appropriate Section Editor * Presented in alphabetical order all the articles will include an explanatory introduction, extensive cross-referencing and an up-to-date bibliography providing literature references for further reading. Presenting state of the art information in a readable, highly accessible style, the scope and coverage provided by the Encyclopedia of Environmetrics will ensure its place as the landmark reference for the many scientists, educators, and decision-makers working across this multidisciplinary field. An essential reference tool for university libraries, research laboratories, government institutions and consultancies concerned with the environmental sciences, the Encyclopedia of Environmetrics brings together for the first time, comprehensive coverage of the full range of topics, techniques and applications covered by this multidisciplinary field. There is currently no central reference source which addresses the needs of this multidisciplinary community. This new Encyclopedia will fill this gap by providing a comprehensive source of relevant fundamental concepts in environmetric research, development and applications for statisticians, mathematicians, economists, environmentalists, ecologist, government officials and policy makers.

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