Multivariate Dependencies
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Multivariate Dependencies
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Author : D.R. Cox
language : en
Publisher: CRC Press
Release Date : 2014-07-22
Multivariate Dependencies written by D.R. Cox and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-22 with Mathematics categories.
Large observational studies involving research questions that require the measurement of several features on each individual arise in many fields including the social and medical sciences. This book sets out both the general concepts and the more technical statistical issues involved in analysis and interpretation. Numerous illustrative examples ar
Multivariate Models And Multivariate Dependence Concepts
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Author : Harry Joe
language : en
Publisher: CRC Press
Release Date : 1997-05-01
Multivariate Models And Multivariate Dependence Concepts written by Harry Joe and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-05-01 with Mathematics categories.
This book on multivariate models, statistical inference, and data analysis contains deep coverage of multivariate non-normal distributions for modeling of binary, count, ordinal, and extreme value response data. It is virtually self-contained, and includes many exercises and unsolved problems.
Dependence Modeling With Copulas
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Author : Harry Joe
language : en
Publisher: CRC Press
Release Date : 2014-06-26
Dependence Modeling With Copulas written by Harry Joe and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-26 with Mathematics categories.
Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.
Encyclopedia Of Quantitative Risk Analysis And Assessment
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Author :
language : en
Publisher: John Wiley & Sons
Release Date : 2008-09-02
Encyclopedia Of Quantitative Risk Analysis And Assessment written by 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 2008-09-02 with Mathematics categories.
Leading the way in this field, the Encyclopedia of Quantitative Risk Analysis and Assessment is the first publication to offer a modern, comprehensive and in-depth resource to the huge variety of disciplines involved. A truly international work, its coverage ranges across risk issues pertinent to life scientists, engineers, policy makers, healthcare professionals, the finance industry, the military and practising statisticians. Drawing on the expertise of world-renowned authors and editors in this field this title provides up-to-date material on drug safety, investment theory, public policy applications, transportation safety, public perception of risk, epidemiological risk, national defence and security, critical infrastructure, and program management. This major publication is easily accessible for all those involved in the field of risk assessment and analysis. For ease-of-use it is available in print and online.
Uncertainty Modeling And Decision Making In Geotechnics
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Author : Kok-Kwang Phoon
language : en
Publisher: CRC Press
Release Date : 2023-12-11
Uncertainty Modeling And Decision Making In Geotechnics written by Kok-Kwang Phoon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-11 with Technology & Engineering categories.
Uncertainty, Modeling, and Decision Making in Geotechnics shows how uncertainty quantification and numerical modeling can complement each other to enhance decision-making in geotechnical practice, filling a critical gap in guiding practitioners to address uncertainties directly. The book helps practitioners acquire a working knowledge of geotechnical risk and reliability methods and guides them to use these methods wisely in conjunction with data and numerical modeling. In particular, it provides guidance on the selection of realistic statistics and a cost-effective, accessible method to address different design objectives, and for different problem settings, and illustrates the value of this to decision-making using realistic examples. Bringing together statistical characterization, reliability analysis, reliability-based design, probabilistic inverse analysis, and physical insights drawn from case studies, this reference guide from an international team of experts offers an excellent resource for state-of-the-practice uncertainty-informed geotechnical design for specialist practitioners and the research community.
Visualization And Imputation Of Missing Values
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Author : Matthias Templ
language : en
Publisher: Springer Nature
Release Date : 2023-11-29
Visualization And Imputation Of Missing Values written by Matthias Templ and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-29 with Mathematics categories.
This book explores visualization and imputation techniques for missing values and presents practical applications using the statistical software R. It explains the concepts of common imputation methods with a focus on visualization, description of data problems and practical solutions using R, including modern methods of robust imputation, imputation based on deep learning and imputation for complex data. By describing the advantages, disadvantages and pitfalls of each method, the book presents a clear picture of which imputation methods are applicable given a specific data set at hand. The material covered includes the pre-analysis of data, visualization of missing values in incomplete data, single and multiple imputation, deductive imputation and outlier replacement, model-based methods including methods based on robust estimates, non-linear methods such as tree-based and deep learning methods, imputation of compositional data, imputation quality evaluation from visual diagnostics to precision measures, coverage rates and prediction performance and a description of different model- and design-based simulation designs for the evaluation. The book also features a topic-focused introduction to R and R code is provided in each chapter to explain the practical application of the described methodology. Addressed to researchers, practitioners and students who work with incomplete data, the book offers an introduction to the subject as well as a discussion of recent developments in the field. It is suitable for beginners to the topic and advanced readers alike.
Bilinear Regression Analysis
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Author : Dietrich von Rosen
language : en
Publisher: Springer
Release Date : 2018-08-02
Bilinear Regression Analysis written by Dietrich von Rosen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-02 with Mathematics categories.
This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. This monograph is of interest to researchers and Ph.D. students in mathematical statistics, signal processing and other fields where statistical multivariate analysis is utilized. It can also be used as a text for second graduate-level courses on multivariate analysis.
S
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Author : R. A. Becker
language : en
Publisher: CRC Press
Release Date : 1984-02-01
S written by R. A. Becker and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-02-01 with Mathematics categories.
The latest edition of this manual provides documentation for users of the statistical software system S.
Stochastic Ageing And Dependence For Reliability
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Author : Chin Diew Lai
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-24
Stochastic Ageing And Dependence For Reliability written by Chin Diew Lai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-24 with Mathematics categories.
Ageing and dependence are two important characteristics in reliability and survival analysis, and they affect significantly the decision people make with regard to maintenance, repair/replacement, price setting, warranties, medical studies, and other areas. There are many papers published at different technical levels. This book aims at providing a state-of-the-art review of the subject so the interested readers may have a panoramic view of the theory and applications of the two areas. This book serves as reference book for professors and researchers involved in reliability and survival analysis. Students with basic probability and statistics knowledge interested in applications will also find the book useful. From the reviews: "This book is an important addition to several well-written books on reliability theory and concepts. The book fulfills the authors aim in providing a comprehensive treatment of both ageing and dependence concepts, with emphasis on reliability and survival analysis....Overall, I recommend this book to all serious-minded researchers, practitioners, teachers, and graduate students who would like to have the most up-to-date information available on the subject of stochastic ageing and dependencies in reliability. It also serves as reference book on reliability and survival analysis and is a good addition to one's statistical or reliability library." Suprasad V. Amari, International Journal of Performability Engineering, Vol. 3, No. 2, April 2007
Markov Networks In Evolutionary Computation
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Author : Siddhartha Shakya
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-04-23
Markov Networks In Evolutionary Computation written by Siddhartha Shakya and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-23 with Computers categories.
Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs). EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis. This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current research trends and future perspectives in the enhancement and applicability of EDAs are also covered. The contributions included in the book address topics as relevant as the application of probabilistic-based fitness models, the use of belief propagation algorithms in EDAs and the application of Markov network based EDAs to real-world optimization problems. The book should be of interest to researchers and practitioners from areas such as optimization, evolutionary computation, and machine learning.