Download or read book On Model Uncertainty and its Statistical Implications written by Theo K. Dijkstra and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.
Download or read book On Model Uncertainty and Its Statistical Implications written by Theo K. Dijkstra and published by . This book was released on 1988 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Uncertainty written by William Briggs and published by Springer. This book was released on 2016-07-15 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance." The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, such as out-of-the-box regression, cannot help in discovering cause. This new way of looking at uncertainty ties together disparate fields — probability, physics, biology, the “soft” sciences, computer science — because each aims at discovering cause (of effects). It broadens the understanding beyond frequentist and Bayesian methods to propose a Third Way of modeling.
Download or read book Accounting for Model Uncertainty in Linear Mixed effects Models written by Adam P. Sima and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Standard statistical decision-making tools, such as inference, confidence intervals and forecasting, are contingent on the assumption that the statistical model used in the analysis is the true model. In linear mixed-effect models, ignoring model uncertainty results in an underestimation of the residual variance, contributing to hypothesis tests that demonstrate larger than nominal Type-I errors and confidence intervals with smaller than nominal coverage probabilities. A novel utilization of the generalized degrees of freedom developed by Zhang et al. (2012) is used to adjust the estimate of the residual variance for model uncertainty. Additionally, the general global linear approximation is extended to linear mixed-effect models to adjust the standard errors of the parameter estimates for model uncertainty. Both of these methods use a perturbation method for estimation, where random noise is added to the response variable and, conditional on the observed responses, the corresponding estimate is calculated. A simulation study demonstrates that when the proposed methodologies are utilized, both the variance and standard errors are inflated for model uncertainty. However, when a data-driven strategy is employed, the proposed methodologies show limited usefulness. These methods are evaluated with a trial assessing the performance of cervical traction in the treatment of cervical radiculopathy.
Download or read book Principles of Uncertainty written by Joseph B. Kadane and published by CRC Press. This book was released on 2020-11-25 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the first edition: Principles of Uncertainty is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. ... the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. ... A must-read for sure!—Christian Robert, CHANCE It's a lovely book, one that I hope will be widely adopted as a course textbook. —Michael Jordan, University of California, Berkeley, USA Like the prize-winning first edition, Principles of Uncertainty, Second Edition is an accessible, comprehensive text on the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples. It presents an introduction to the subjective Bayesian approach which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. This new edition has been updated throughout and features new material on Nonparametric Bayesian Methods, the Dirichlet distribution, a simple proof of the central limit theorem, and new problems. Key Features: First edition won the 2011 DeGroot Prize Well-written introduction to theory of Bayesian statistics Each of the introductory chapters begins by introducing one new concept or assumption Uses "just-in-time mathematics"—the introduction to mathematical ideas just before they are applied
Download or read book Applied Research in Uncertainty Modeling and Analysis written by Bilal M. Ayyub and published by Springer Science & Business Media. This book was released on 2007-12-29 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application areas of uncertainty are numerous and diverse, including all fields of engineering, computer science, systems control and finance. Determining appropriate ways and methods of dealing with uncertainty has been a constant challenge. The theme for this book is better understanding and the application of uncertainty theories. This book, with invited chapters, deals with the uncertainty phenomena in diverse fields. The book is an outgrowth of the Fourth International Symposium on Uncertainty Modeling and Analysis (ISUMA), which was held at the center of Adult Education, College Park, Maryland, in September 2003. All of the chapters have been carefully edited, following a review process in which the editorial committee scrutinized each chapter. The contents of the book are reported in twenty-three chapters, covering more than . . ... pages. This book is divided into six main sections. Part I (Chapters 1-4) presents the philosophical and theoretical foundation of uncertainty, new computational directions in neural networks, and some theoretical foundation of fuzzy systems. Part I1 (Chapters 5-8) reports on biomedical and chemical engineering applications. The sections looks at noise reduction techniques using hidden Markov models, evaluation of biomedical signals using neural networks, and changes in medical image detection using Markov Random Field and Mean Field theory. One of the chapters reports on optimization in chemical engineering processes.
Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach and published by Emerald Group Publishing. This book was released on 2008-02-29 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.
Download or read book Understanding Uncertainty written by Dennis V. Lindley and published by John Wiley & Sons. This book was released on 2013-12-16 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...a reference for everyone who is interested in knowing and handling uncertainty." —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 go-to guide for uncertainty and decision making, providing further applications at an accessible level including: A critical study of transitivity, a basic concept in probability A discussion of how the failure of the financial sector to use the proper approach to uncertainty may have contributed to the recent recession A consideration of betting, showing that a bookmaker's odds are not expressions of probability Applications of the book’s thesis to statistics A demonstration that some techniques currently popular in statistics, like significance tests, may be unsound, even seriously misleading, because they violate the rules of probability Understanding Uncertainty, Revised Edition is ideal for students studying probability or statistics and for anyone interested in one of the most fascinating and vibrant fields of study in contemporary science and mathematics.
Download or read book The Uncertainty Analysis of Model Results written by Eduard Hofer and published by Springer. This book was released on 2018-05-02 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.
Download or read book Estimating and Correcting the Effects of Model Selection Uncertainty written by and published by Cuvillier Verlag. This book was released on 2006-04-24 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most applied statistical analyses are carried out under model uncertainty, meaning that the model which generated the observations is unknown, and so the data are first used to select one of a set of plausible models by means of some selection criterion. Generally the data are then used to make inferences about some quantity of interest, ignoring model selection uncertainty, i.e. the fact that the selection step was carried out using the same data, and despite the known fact that this leads to invalid inferences. This thesis investigates several issues relating to this problem from both the Bayesian and the frequentist points of view, and offers new suggestions for dealing with it. We examine Bayesian model averaging (BMA) and point out that its frequentist performance is not always well-defined because, in some cases, it is unclear whether BMA methodology is truly Bayesian. We illustrate the point with a “fully Bayesian model averaging" that is applicable when the quantity of interest is parametric.
Download or read book Artificial Neural Networks written by Kevin L. Priddy and published by SPIE Press. This book was released on 2005 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed, and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks.
Download or read book The Labor Market and Business Cycle Theories written by Piero Ferri and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in business cycles has had its 'ups and downs'. After a period of almost steady state growth and of economic tranquility, when the business cycle seemed to be obsolete, the turbulence of the 70s and 80s has contributedto a renewed interest in the topic. Important analytical and methodological innovations have also favored the present abundance of contributions. Four innovations are of particular importance: i. microfoundations ii. nonlinearities iii. stochastic variables iv. real aspects. Both Classical macroeconomics and new-Keynesian approaches seem to share these characteristics, which apply both to endogenous and exogenous explanations of the cycle. The distance separating the newer literature from its forebears seems vast. Previously, cycle theory was characterized by a macro approach and utilized nonlinearities either through piecewise 'linear models or with the aid of Classical theorems in the field of dynamic systems. To consider and to compare the old and the new literature on business cycles is one of the goals of this book. To narrow the distance separating them is another goal of this research. We do not try to bridge it, but rather to revisit the former tradition with new tools. Finally, a particular emphasis is put on the 'ceilings and floors' type of literature. One of us has written a D. Phil. thesis with Sir John Hicks, and both have worked with H. P. Minsky. Hicks, along with Goodwin, introdu. ced the concept of ceilings and floors into business cycle analysis, and Minsky made important contributions to the area.
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 The Elements of a Nonlinear Theory of Economic Dynamics written by Carl Chiarella and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elements of a Nonlinear Theory of Economic Dynamics provides both a framework and a survey of its needs. First, principle results and techniques of the theory relevant to applications in dynamic economics are discussed, then their application in view of older endogenous cycle theories are considered in a unified mathematical framework. Models incorporating the government budget constraint and the Goodwin model are analysed using the method of averaging and the centre manifold theory. The dynamic instability problem is solved by placing models in a nonlinear framework.
Download or read book Binary Functions and their Applications written by Horand Störmer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book binary functions and their representation by implicants or implicates are described. In particular minimal representations by prime implicants or prime implicates are given. Such representations generalize the minimal representations of the usual Boolean functions. It is shown that implicants (implicates) of discrete functions may be constructed with the help of implicants (implicates) of binary functions. One substantial application is the description of the reliability structure of technical systems, another is the use of binary respectively discrete functions to classify objects which are described by the grades of certain attributes. Finally a class of Boolean algebras of practical importance (set algebras, indicator algebras, algebras of classes of propositions) are considered. The elements of such algebras have representations which are strongly connected with the representations of binary functions.
Download or read book Machine Learning and Knowledge Discovery in Databases written by Michele Berlingerio and published by Springer. This book was released on 2019-01-17 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume proceedings LNAI 11051 – 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
Download or read book Stochastic Musings written by John Panaretos and published by Psychology Press. This book was released on 2014-05-22 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edited volume features contributions from many of the leading scientists in probability and statistics from the latter part of the 20th century. It is the only book to assemble the views of these leading scientists--the pioneers in their respective fields. Stochastic Musings features contributions by: *Sir David Cox on statistics and econometrics; *C.R. Rao, M.B. Rao, and D.N. Shanbhag on convex sets of multivariate distributions and their extreme points; *Bradley Efron on the future of statistics; *David Freedman on regression association and causation; *Vic Barnett on sample ordering for effective statistical inference with particular reference to environmental issues; *David Bartholomew on a unified statistical approach to some measurement problems in the social sciences; *Joe Gani on scanning a lattice for a particular pattern; *Leslie Kish on new paradigms for probability sampling (his last paper); *Samuel Kotz and Norman L. Johnson on limit distributions of uncorrelated but dependent distributions on the unit square; *Samuel Kotz and Saralees Nadarajah on some new elliptical distributions; *Jef Teugels on the life span of a renewal; *Wolfgang Urfer and Katharina Emrich on maximum likelihood estimates of genetic effects; and **Vladimir M. Zolotarev on convergence rate estimates in functional limit theorems. The volume also includes the following contributions by faculty members of the Department of Statistics, Athens University of Economics and Business: *J. Panaretos, E. Xekalaki, and S. Psarakis on a predictive model evaluation and selection approach--the correlated gamma ratio distribution; *J. Panaretos and Z. Tsourti on extreme value index estimators and smoothing alternatives; *E. Xekalaki and D. Karlis on mixtures everywhere; and * Ir. Moustaki on latent variable models with covariates. Stochastic Musings will appeal to researchers, professionals, and students interested in the history and development of statistics and probability as well as in related areas, such as physics, biometry, economics, and mathematics. Academic and professional statisticians will benefit from the book's coverage of the latest developments in the field, as well as reflections on the future directions of the discipline.
