Statistical Meta Analysis With Applications Wiley Series In Probability And Statistics
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Statistical Meta Analysis With Applications Wiley Series In Probability And Statistics
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Author : Guido Knapp
language : en
Publisher:
Release Date : 2008
Statistical Meta Analysis With Applications Wiley Series In Probability And Statistics written by Guido Knapp and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Statistical Meta Analysis With Applications
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Author : Joachim Hartung
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Statistical Meta Analysis With Applications written by Joachim Hartung and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Medical categories.
An accessible introduction to performing meta-analysis across various areas of research The practice of meta-analysis allows researchers to obtain findings from various studies and compile them to verify and form one overall conclusion. Statistical Meta-Analysis with Applications presents the necessary statistical methodologies that allow readers to tackle the four main stages of meta-analysis: problem formulation, data collection, data evaluation, and data analysis and interpretation. Combining the authors' expertise on the topic with a wealth of up-to-date information, this book successfully introduces the essential statistical practices for making thorough and accurate discoveries across a wide array of diverse fields, such as business, public health, biostatistics, and environmental studies. Two main types of statistical analysis serve as the foundation of the methods and techniques: combining tests of effect size and combining estimates of effect size. Additional topics covered include: Meta-analysis regression procedures Multiple-endpoint and multiple-treatment studies The Bayesian approach to meta-analysis Publication bias Vote counting procedures Methods for combining individual tests and combining individual estimates Using meta-analysis to analyze binary and ordinal categorical data Numerous worked-out examples in each chapter provide the reader with a step-by-step understanding of the presented methods. All exercises can be computed using the R and SAS software packages, which are both available via the book's related Web site. Extensive references are also included, outlining additional sources for further study. Requiring only a working knowledge of statistics, Statistical Meta-Analysis with Applications is a valuable supplement for courses in biostatistics, business, public health, and social research at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians working in industry, academia, and government.
New Frontiers In Statistics And Data Science
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Author : Lígia Henriques-Rodrigues
language : en
Publisher: Springer Nature
Release Date : 2025-01-10
New Frontiers In Statistics And Data Science written by Lígia Henriques-Rodrigues and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-10 with Mathematics categories.
This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023). It covers a wide range of cutting-edge topics in both theoretical and applied statistics. Each contribution highlights the latest advancements and research in the field, offering valuable insights and innovative methodologies for researchers and practitioners alike. Readers with a background in mathematics and statistics will find it particularly beneficial, while researchers from various scientific disciplines can explore numerous robust applications.
Novelty Information And Surprise
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Author : Günther Palm
language : en
Publisher: Springer Nature
Release Date : 2023-01-02
Novelty Information And Surprise written by Günther Palm and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-02 with Mathematics categories.
This revised edition offers an approach to information theory that is more general than the classical approach of Shannon. Classically, information is defined for an alphabet of symbols or for a set of mutually exclusive propositions (a partition of the probability space Ω) with corresponding probabilities adding up to 1. The new definition is given for an arbitrary cover of Ω, i.e. for a set of possibly overlapping propositions. The generalized information concept is called novelty and it is accompanied by two concepts derived from it, designated as information and surprise, which describe "opposite" versions of novelty, information being related more to classical information theory and surprise being related more to the classical concept of statistical significance. In the discussion of these three concepts and their interrelations several properties or classes of covers are defined, which turn out to be lattices. The book also presents applications of these concepts, mostly in statistics and in neuroscience.
A Practical Guide To Data Mining For Business And Industry
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Author : Andrea Ahlemeyer-Stubbe
language : en
Publisher: John Wiley & Sons
Release Date : 2014-03-31
A Practical Guide To Data Mining For Business And Industry written by Andrea Ahlemeyer-Stubbe and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-31 with Mathematics categories.
Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.
Handbook Of Monte Carlo Methods
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Author : Dirk P. Kroese
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-06
Handbook Of Monte Carlo Methods written by Dirk P. Kroese and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-06 with Mathematics categories.
A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.
The Semantic Web Eswc 2012 Satellite Events
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Author : Elena Simperl
language : en
Publisher: Springer
Release Date : 2015-04-20
The Semantic Web Eswc 2012 Satellite Events written by Elena Simperl and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-20 with Computers categories.
This book constitutes the thoroughly refereed post-proceedings of the satellite events of the 9th International Conference on the Semantic Web, ESWC 2012, held in Heraklion, Crete, Greece, in May 2012. This volume contains 49 full papers and 13 short papers describing the posters and demonstrations. (SUGGESTION/ HELP needed).
Optimal Learning
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Author : Warren B. Powell
language : en
Publisher: John Wiley & Sons
Release Date : 2013-07-09
Optimal Learning written by Warren B. Powell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-09 with Mathematics categories.
Learn the science of collecting information to make effective decisions Everyday decisions are made without the benefit of accurate information. Optimal Learning develops the needed principles for gathering information to make decisions, especially when collecting information is time-consuming and expensive. Designed for readers with an elementary background in probability and statistics, the book presents effective and practical policies illustrated in a wide range of applications, from energy, homeland security, and transportation to engineering, health, and business. This book covers the fundamental dimensions of a learning problem and presents a simple method for testing and comparing policies for learning. Special attention is given to the knowledge gradient policy and its use with a wide range of belief models, including lookup table and parametric and for online and offline problems. Three sections develop ideas with increasing levels of sophistication: Fundamentals explores fundamental topics, including adaptive learning, ranking and selection, the knowledge gradient, and bandit problems Extensions and Applications features coverage of linear belief models, subset selection models, scalar function optimization, optimal bidding, and stopping problems Advanced Topics explores complex methods including simulation optimization, active learning in mathematical programming, and optimal continuous measurements Each chapter identifies a specific learning problem, presents the related, practical algorithms for implementation, and concludes with numerous exercises. A related website features additional applications and downloadable software, including MATLAB and the Optimal Learning Calculator, a spreadsheet-based package that provides an introduction to learning and a variety of policies for learning.
Theoretical Foundations Of Functional Data Analysis With An Introduction To Linear Operators
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Author : Tailen Hsing
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-07
Theoretical Foundations Of Functional Data Analysis With An Introduction To Linear Operators written by Tailen Hsing and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-07 with Mathematics categories.
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA). The self–contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self–adjoint and non self–adjoint operators. The probabilistic foundation for FDA is described from the perspective of random elements in Hilbert spaces as well as from the viewpoint of continuous time stochastic processes. Nonparametric estimation approaches including kernel and regularized smoothing are also introduced. These tools are then used to investigate the properties of estimators for the mean element, covariance operators, principal components, regression function and canonical correlations. A general treatment of canonical correlations in Hilbert spaces naturally leads to FDA formulations of factor analysis, regression, MANOVA and discriminant analysis. This book will provide a valuable reference for statisticians and other researchers interested in developing or understanding the mathematical aspects of FDA. It is also suitable for a graduate level special topics course.
Sampling
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Author : Steven K. Thompson
language : en
Publisher: John Wiley & Sons
Release Date : 2012-02-08
Sampling written by Steven K. Thompson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-08 with Mathematics categories.
Praise for the Second Edition "This book has never had a competitor. It is the only book that takes a broad approach to sampling . . . any good personal statistics library should include a copy of this book." —Technometrics "Well-written . . . an excellent book on an important subject. Highly recommended." —Choice "An ideal reference for scientific researchers and other professionals who use sampling." —Zentralblatt Math Features new developments in the field combined with all aspects of obtaining, interpreting, and using sample data Sampling provides an up-to-date treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hard-to-detect populations. This Third Edition retains the general organization of the two previous editions, but incorporates extensive new material—sections, exercises, and examples—throughout. Inside, readers will find all-new approaches to explain the various techniques in the book; new figures to assist in better visualizing and comprehending underlying concepts such as the different sampling strategies; computing notes for sample selection, calculation of estimates, and simulations; and more. Organized into six sections, the book covers basic sampling, from simple random to unequal probability sampling; the use of auxiliary data with ratio and regression estimation; sufficient data, model, and design in practical sampling; useful designs such as stratified, cluster and systematic, multistage, double and network sampling; detectability methods for elusive populations; spatial sampling; and adaptive sampling designs. Featuring a broad range of topics, Sampling, Third Edition serves as a valuable reference on useful sampling and estimation methods for researchers in various fields of study, including biostatistics, ecology, and the health sciences. The book is also ideal for courses on statistical sampling at the upper-undergraduate and graduate levels.