Measuring Statistical Evidence Using Relative Belief
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Measuring Statistical Evidence Using Relative Belief
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Author : Michael Evans
language : en
Publisher: CRC Press
Release Date : 2015-06-23
Measuring Statistical Evidence Using Relative Belief written by Michael Evans and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-23 with Mathematics categories.
This book provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It attempts to establish a gold standard for how a statistical analysis should proceed. The book illustrates relative belief theory using many examples and describes the strengths and weaknesses of the theory. The author also addresses fundamental statistical issues, including the meaning of probability, the role of subjectivity, the meaning of objectivity, and the role of infinity and continuity.
Symmetry Measures On Complex Networks
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Author : Angel Garrido
language : en
Publisher: MDPI
Release Date : 2018-07-09
Symmetry Measures On Complex Networks written by Angel Garrido and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-09 with Mathematics categories.
This book is a printed edition of the Special Issue "Symmetry Measures on Complex Networks" that was published in Symmetry
Research Integrity
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Author : Lee J. Jussim
language : en
Publisher: Oxford University Press
Release Date : 2022
Research Integrity written by Lee J. Jussim and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Medical categories.
This book offers a behavioral science perspective on how scientific practice becomes compromised and provides recommendations for improvement. Broadening the discussion of research integrity beyond replication, publication biases, statistics, and methods, this book addresses the full complexity of the issue and serves academics and policy makers who are concerned with the reliability and validity of scientific findings across the social sciences
Semialgebraic Statistics And Latent Tree Models
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Author : Piotr Zwiernik
language : en
Publisher: CRC Press
Release Date : 2015-08-21
Semialgebraic Statistics And Latent Tree Models written by Piotr Zwiernik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-21 with Mathematics categories.
The first part of the book gives a general introduction to key concepts in algebraic statistics, focusing on methods that are helpful in the study of models with hidden variables. The author uses tensor geometry as a natural language to deal with multivariate probability distributions, develops new combinatorial tools to study models with hidden data, and describes the semialgebraic structure of statistical models. The second part illustrates important examples of tree models with hidden variables. The book discusses the underlying models and related combinatorial concepts of phylogenetic trees as well as the local and global geometry of latent tree models. It also extends previous results to Gaussian latent tree models. This book shows you how both combinatorics and algebraic geometry enable a better understanding of latent tree models. It contains many results on the geometry of the models, including a detailed analysis of identifiability and the defining polynomial constraints
Handbook Of Approximate Bayesian Computation
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Author : Scott A. Sisson
language : en
Publisher: CRC Press
Release Date : 2018-09-03
Handbook Of Approximate Bayesian Computation written by Scott A. Sisson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Mathematics categories.
As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ABC methods. These simple, but powerful statistical techniques, take Bayesian statistics beyond the need to specify overly simplified models, to the setting where the model is defined only as a process that generates data. This process can be arbitrarily complex, to the point where standard Bayesian techniques based on working with tractable likelihood functions would not be viable. ABC methods finesse the problem of model complexity within the Bayesian framework by exploiting modern computational power, thereby permitting approximate Bayesian analyses of models that would otherwise be impossible to implement. The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an essential reference book for anyone interested in learning about and implementing ABC techniques to analyse complex models in the modern world.
Everything Is Predictable
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Author : Tom Chivers
language : en
Publisher: Simon and Schuster
Release Date : 2025-07-08
Everything Is Predictable written by Tom Chivers and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-08 with Mathematics categories.
A “fascinating, witty, and perspective-shifting” (Oliver Burkeman, New York Times bestselling author) tour of Bayes’s theorem and its global impact on modern life from the acclaimed science writer and author of The Rationalist’s Guide to the Galaxy. At its simplest, Bayes’s theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes’s theorem is a description of almost everything. But who was the man who lent his name to this theorem? How did an 18th-century Presbyterian minister and amateur mathematician uncover a theorem that would affect fields as diverse as medicine, law, and artificial intelligence? “Witty, lively, and best of all, extremely nerdy” (Tim Harford, author of The Undercover Economist), Everything Is Predictable is an entertaining and accessible illustration of how a single compelling idea can have far reaching consequences.
Asymptotic Analysis Of Mixed Effects Models
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Author : Jiming Jiang
language : en
Publisher: CRC Press
Release Date : 2017-09-19
Asymptotic Analysis Of Mixed Effects Models written by Jiming Jiang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-19 with Mathematics categories.
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.
Hidden Markov Models For Time Series
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Author : Walter Zucchini
language : en
Publisher: CRC Press
Release Date : 2017-12-19
Hidden Markov Models For Time Series written by Walter Zucchini and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Mathematics categories.
Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses. After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations. The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations. Features Presents an accessible overview of HMMs Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology Includes numerous theoretical and programming exercises Provides most of the analysed data sets online New to the second edition A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal movement, rainfall occurrence and capture-recapture data
Generalized Linear Models With Random Effects
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Author : Youngjo Lee
language : en
Publisher: CRC Press
Release Date : 2018-07-11
Generalized Linear Models With Random Effects written by Youngjo Lee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-11 with Mathematics categories.
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.
Absolute Risk
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Author : Ruth M. Pfeiffer
language : en
Publisher: CRC Press
Release Date : 2017-08-10
Absolute Risk written by Ruth M. Pfeiffer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-10 with Mathematics categories.
Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients, devising public health strategies, and clinical management. The book provides sufficient technical detail to allow statisticians, epidemiologists, and clinicians to build, test, and apply models of absolute risk. Features: Provides theoretical basis for modeling absolute risk, including competing risks and cause-specific and cumulative incidence regression Discusses various sampling designs for estimating absolute risk and criteria to evaluate models Provides details on statistical inference for the various sampling designs Discusses criteria for evaluating risk models and comparing risk models, including both general criteria and problem-specific expected losses in well-defined clinical and public health applications Describes many applications encompassing both disease prevention and prognosis, and ranging from counseling individual patients, to clinical decision making, to assessing the impact of risk-based public health strategies Discusses model updating, family-based designs, dynamic projections, and other topics Ruth M. Pfeiffer is a mathematical statistician and Fellow of the American Statistical Association, with interests in risk modeling, dimension reduction, and applications in epidemiology. She developed absolute risk models for breast cancer, colon cancer, melanoma, and second primary thyroid cancer following a childhood cancer diagnosis. Mitchell H. Gail developed the widely used "Gail model" for projecting the absolute risk of invasive breast cancer. He is a medical statistician with interests in statistical methods and applications in epidemiology and molecular medicine. He is a member of the National Academy of Medicine and former President of the American Statistical Association. Both are Senior Investigators in the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health.