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Probability & Statistics - Bayesian Analysis

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Probability, Choice, and Reason
by Williams, Leighton Vaughan       
(Paperback - English - 9780367538910)
Much of our thinking is flawed because it is based on faulty intuition. By using the framework and tools of probability and statistics, we can overcome this to provide solutions to many real-world problems and paradoxes. We show how to do this, and find answers that are frequently very contrary to what we might expect. Along the way, we venture into diverse realms and thought experiments which challenge the way that we see the world. Features: ul li An insightful and engaging discussion of some of the key ideas of probabilistic and statistical thinking li li Many classic and novel problems, paradoxes, and puzzles li li An exploration of some o ..
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Probability, Choice, and Reason
by Williams, Leighton Vaughan       
(Hardcover - English - 9780367538934)
Much of our thinking is flawed because it is based on faulty intuition. By using the framework and tools of probability and statistics, we can overcome this to provide solutions to many real-world problems and paradoxes. We show how to do this, and find answers that are frequently very contrary to what we might expect. Along the way, we venture into diverse realms and thought experiments which challenge the way that we see the world. Features: ul li An insightful and engaging discussion of some of the key ideas of probabilistic and statistical thinking li li Many classic and novel problems, paradoxes, and puzzles li li An exploration of some o ..
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Rp. 4.661.000
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Conditional Measures and Applications
by Rao, M. M.    Taft, Earl    Nashed, Zuhair
(Hardcover - English - 9781574445930)
In response to unanswered difficulties in the generalized case of conditional expectation and to treat the topic in a well-deservedly thorough manner, M.M. Rao gave us the highly successful first edition of Conditional Measures and Applications. Until this groundbreaking work, conditional probability was relegated to scattered journal articles and mere chapters in larger works on probability. This second edition continues to offer a thorough treatment of conditioning while adding substantial new information on developments and applications that have emerged over the past decade. Conditional Measures and Applications, Second Edition clearly elucidates the subjec ..
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Probability, Statistics, and Stochastic Processes for Engineers and Scientists
by Haghighi, Aliakbar Montazer    Wickramasinghe, Indika   
(Paperback - English - 9780367500863)
strong 2020 Taylor & Francis Award Winner for Outstanding New Textbook! strong Featuring recent advances in the field, this new textbook presents probability and statistics, and their applications in stochastic processes. This book presents key information for understanding the essential aspects of basic probability theory and concepts of reliability as an application. The purpose of this book is to provide an option in this field that combines these areas in one book, balances both theory and practical applications, and also keeps the practitioners in mind. Features ul li Includes numerous examples using current technologies with applications in va ..
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Bayesian Optimization with Application to Computer Experiments
by Pourmohamad, Tony    K. H. Lee, Herbert   
(Paperback - English - 9783030824570)
This book introduces readers to Bayesian optimization, highlighting advances in the field and showcasing its successful applications to computer experiments. R code is available as online supplementary material for most included examples, so that readers can better comprehend and reproduce methods. Compact and accessible, the volume is broken down into four chapters. Chapter 1 introduces the reader to the topic of computer experiments; it includes a variety of examples across many industries. Chapter 2 focuses on the task of surrogate model building and contains a mix of several different surrogate models that are used in the computer modeling and machine lear ..
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An Introduction to Bayesian Inference, Methods and Computation
by Heard, Nick       
(Hardcover - English - 9783030828073)
These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches. br ..
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Multi-Level Bayesian Models for Environment Perception
by Benedek, Csaba       
(Hardcover - English - 9783030836535)
Introduction.- Fundamentals. - Bayesian models for Dynamic Scene Analysis.- Multi-layer label fusion models.- Multitemporal data analysis with Marked Point Processes. - Multi-level object population analysis with an EMPP model.- Concluding Remarks.- References.- Index. ..
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Bayesian Modeling of Spatio-Temporal Data with R
by Sahu, Sujit       
(Hardcover - English - 9780367277987)
Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide ranging inference and prediction. Ideally such inferential tasks should be approached through modelling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modelling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems. Key features of the book: - Accessible d ..
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Introducing Financial Mathematics: Theory, Binomial Models, and Applications
by Wickerhauser, Mladen Victor       
(Hardcover - English - 9781032359854)
strong Introducing Financial Mathematics: Theory, Binomial Models, and Applications strong seeks to replace existing books with a rigorous stand-alone text that covers fewer examples in greater detail with more proofs. The book uses the fundamental theorem of asset pricing as an introduction to linear algebra and convex analysis. It also provides example computer programs, mainly Octave MATLAB functions but also spreadsheets and Macsyma scripts, with which students may experiment on real data.The text's unique coverage is in its contemporary combination of discrete and continuous models to compute implied volatility and fit models to market data. The goal is ..
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Bayesian Reasoning and Gaussian Processes for Machine Learning Applications
by K, Hemachandran    Tayal, Shubham    George, Preetha Mary
(Hardcover - English - 9780367758479)
This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game development, decision making, and drug discovery. It is very effective for machine learning algorithms in handling missing data and extracting information from small datasets. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning, which is followed ..
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Theory of Stochastic Objects: Probability, Stochastic Processes and Inference
by Micheas, Athanasios Christou       
(Paperback - English - 9781032242880)
This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks; one would need material on real analysis, measure and probability theory, as well as stochastic processes - in addition to at least one text on statistics- to capture the detail and depth of material that has gone into this volume. ul li Presents and illustrates 'random objects' in different contexts, under a unified framework, starting with rudimentary results on rand ..
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Nonlinear Mixture Models: A Bayesian Approach
by Tatarinova, Tatiana V.    Schumitzky, Alan   
(Hardcover - English - 9781848167568)
This book, strong written by two mathematicians from the University of Southern California strong , provides a broad introduction to the important subject of nonlinear mixture models from a Bayesian perspective. It contains background material, a brief description of Markov chain theory, as well as novel algorithms and their applications. It is self-contained and unified in presentation, which makes it ideal for use as an advanced textbook by graduate students and as a reference for independent researchers. The explanations in the book are detailed enough to capture the interest of the curious reader, and complete enough to provide the necessary background m ..
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Bayesian Analysis for Population Ecology
by King, Ruth    Morgan, Byron    Gimenez, Olivier
(Hardcover - English - 9781439811870)
Novel Statistical Tools for Conserving and Managing Populations By gathering information on key demographic parameters, scientists can often predict how populations will develop in the future and relate these parameters to external influences, such as global warming. Because of their ability to easily incorporate random effects, fit state-space models, evaluate posterior model probabilities, and deal with missing data, modern Bayesian methods have become important in this area of statistical inference and forecasting. Emphasising model choice and model averaging, strong Bayesian Analysis for Population Ecology strong presents up-to-date methods for anal ..
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Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives: An Essential Journey with Donald Rubin's Statistical Family
by Gelman, Andrew    Meng, Xiao-Li   
(Hardcover - English - 9780470090435)
This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: ul li Comprehensive coverage of an imporant area for both research and applications. li li Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techn ..
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Understanding Uncertainty
by Lindley, Dennis V.       
(Hardcover - English - 9781118650127)
Praise for the First Edition "...a reference for everyone who is interested in knowing and handling uncertainty." br --Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made. Featuring new material, the Revised Edition remains the g ..
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Information Processing: Boolean Algebra, Classical Logic, Cellular Automata, and Probability Manipulation
by Blower, David J.       
(Paperback - English - 9781460938386)
Volumewas corrected and revised in September 2017. This book begins the task of defining, explaining, arguing for, and, in the end, providing a rationale for information processing. Volumeis concerned with the notion that an information processor is mainly engaged in making inferences. An information processor would prefer to reach definite conclusions by using some form of deduction. Unfortunately, it is often thwarted in this desire by a fundamental lack of relevant information. Probability theory has developed as a rigorous way of dealing with the uncertainty surrounding inference. Thus, we begin by treating some of the formal manipulation rules that crop up ..
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Probability and Stochastic Modeling
by Rotar, Vladimir I.       
(Hardcover - English - 9781439872062)
strong Probability and Stochastic Modeling strong not only covers all the topics found in a traditional introductory probability course, but also emphasizes stochastic modeling, including Markov chains, birth-death processes, and reliability models. Unlike most undergraduate-level probability texts, the book also focuses on increasingly important areas, such as martingales, classification of dependency structures, and risk evaluation. Numerous examples, exercises, and models using real-world data demonstrate the practical possibilities and restrictions of different approaches and help students grasp general concepts and theoretical results. The text is suitab ..
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Entendiendo Las Probabilidades Y Calculándolas: Fundamentos de la Teoría de la Probabilidad y Guía de Cálculo Para Principiantes, con Aplicaciones en
by Barboianu, Catalin    Martilotti, Rafael   
(Paperback - Spanish - 9789731991061)
La vida cotidiana est llena de situaciones que exigen tomar decisiones. Y en estos casos comparamos y hacemos estimaciones de probabilidades, a veces casi sin darnos cuenta, especialmente en el momento de decidir. Pero las probabilidades no son n meros simples asociados objetiva o subjetivamente a los eventos, como nos podr a parecer, y el c lculo y el uso que le damos est n especialmente proclives a errores cualitativos y cuantitativos, si no se maneja un conocimiento apropiado. Por ello es una necesidad que exista un libro que explique el concepto de probabilidad junto con sus interpretaciones y aplicaciones, dirigido a gente sin conocimientos profundos de ma ..
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Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition
by Sheskin, David J.       
(Hardcover - English - 9781439858011)
Following in the footsteps of its bestselling predecessors, the strong Handbook of Parametric and Nonparametric Statistical strong strong r strong strong ocedures, Fifth Edition strong provides researchers, teachers, and students with an all-inclusive reference on univariate, bivariate, and multivariate statistical procedures. strong New in the Fifth Edition: strong ul li Substantial updates and new material throughout li li New chapters on path analysis, meta-analysis, and structural equation modeling li li Index numbers and time series analysis applications in business and economics li li Statistical quality control applications in ind ..
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Special Order
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Introduction to Stochastic Processes
by Lawler, Gregory F.       
(Hardcover - English - 9781584886518)
Emphasizing fundamental mathematical ideas rather than proofs, Introduction to Stochastic Processes, Second Edition provides quick access to important foundations of probability theory applicable to problems in many fields. Assuming that you have a reasonable level of computer literacy, the ability to write simple programs, and the access to software for linear algebra computations, the author approaches the problems and theorems with a focus on stochastic processes evolving with time, rather than a particular emphasis on measure theory. For those lacking in exposure to linear differential and difference equations, the author begins with a brief introduction to ..
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