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Applied Nonparametric Statistics in Reliability

Author : M. Luz Gámiz

Publisher : Springer Science & Business Media

Page : 238 pages

File Size : 24,2 MB

Release : 2011-02-14

Category : Technology & Engineering

ISBN : 0857291181

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Book Description

Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric analyses in reliability currently form an interesting area of study that has not yet been fully explored. Applied Nonparametric Statistics in Reliability is focused on the use of modern statistical methods for the estimation of dependability measures of reliability systems that operate under different conditions. The scope of the book includes: smooth estimation of the reliability function and hazard rate of non-repairable systems; study of stochastic processes for modelling the time evolution of systems when imperfect repairs are performed; nonparametric analysis of discrete and continuous time semi-Markov processes; isotonic regression analysis of the structure function of a reliability system, and lifetime regression analysis. Besides the explanation of the mathematical background, several numerical computations or simulations are presented as illustrative examples. The corresponding computer-based methods have been implemented using R and MATLAB®. A concrete modelling scheme is chosen for each practical situation and, in consequence, a nonparametric inference procedure is conducted. Applied Nonparametric Statistics in Reliability will serve the practical needs of scientists (statisticians and engineers) working on applied reliability subjects.



Nonparametric Statistics with Applications to Science and Engineering

Author : Paul H. Kvam

Publisher : John Wiley & Sons

Page : 448 pages

File Size : 20,38 MB

Release : 2007-08-24

Category : Mathematics

ISBN : 9780470168691

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Book Description

A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.





Statistical Methods for Reliability Data

Author : William Q. Meeker

Publisher : John Wiley & Sons

Page : 708 pages

File Size : 36,21 MB

Release : 2022-01-24

Category : Technology & Engineering

ISBN : 1118594487

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Book Description

An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook. The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data. SMRD2 features: Contains a wealth of information on modern methods and techniques for reliability data analysis Offers discussions on the practical problem-solving power of various Bayesian inference methods Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.



Applied Bayesian Forecasting and Time Series Analysis

Author : Andy Pole

Publisher : CRC Press

Page : 432 pages

File Size : 16,49 MB

Release : 2018-10-08

Category : Business & Economics

ISBN : 1482267438

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Book Description

Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for forecasting and the analysis of time series. The authors unify the concepts, model forms, and modeling requirements within the framework of the dynamic linear mode (DLM). They include a complete theoretical development of the DLM and illustrate each step with analysis of time series data. Using real data sets the authors: Explore diverse aspects of time series, including how to identify, structure, explain observed behavior, model structures and behaviors, and interpret analyses to make informed forecasts Illustrate concepts such as component decomposition, fundamental model forms including trends and cycles, and practical modeling requirements for routine change and unusual events Conduct all analyses in the BATS computer programs, furnishing online that program and the more than 50 data sets used in the text The result is a clear presentation of the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations. Accessible to undergraduates, this unique volume also offers complete guidelines valuable to researchers, practitioners, and advanced students in statistics, operations research, and engineering.



Applied Stochastic Modelling

Author : Byron J.T. Morgan

Publisher : CRC Press

Page : 363 pages

File Size : 46,32 MB

Release : 2008-12-02

Category : Mathematics

ISBN : 1420011650

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Book Description

Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and



Applied Nonparametric Econometrics

Author : Daniel J. Henderson

Publisher : Cambridge University Press

Page : 381 pages

File Size : 46,5 MB

Release : 2015-01-12

Category : Business & Economics

ISBN : 1316060675

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Book Description

The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.



Geotechnical and Geophysical Site Characterization

Author : An-Bin Huang

Publisher : CRC Press

Page : 260 pages

File Size : 30,15 MB

Release : 2008-04-04

Category : Science

ISBN : 0203883195

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Book Description

Geotechnical and Geophysical Site Characterization collects the papers presented at the Third International Conference on Site Characterization (ISC 3) that took place in Taipei from April 1-4, 2008. The subjects covered include new developments in mechanical in-situ testing and interpretation techniques, statistical analysis of test data, geo



An Introduction to Modern Nonparametric Statistics

Author : James J. Higgins

Publisher : Duxbury Resource Center

Page : 0 pages

File Size : 23,38 MB

Release : 2004

Category : Nonparametric statistics

ISBN : 9780534387754

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Book Description

Guided by problems that frequently arise in actual practice, James Higgins' book presents a wide array of nonparametric methods of data analysis that researchers will find useful. It discusses a variety of nonparametric methods and, wherever possible, stresses the connection between methods. For instance, rank tests are introduced as special cases of permutation tests applied to ranks. The author provides coverage of topics not often found in nonparametric textbooks, including procedures for multivariate data, multiple regression, multi-factor analysis of variance, survival data, and curve smoothing. This truly modern approach teaches non-majors how to analyze and interpret data with nonparametric procedures using today's computing technology.



Doing Research in Business and Management

Author : Dan Remenyi

Publisher : SAGE

Page : 320 pages

File Size : 45,82 MB

Release : 1998-09-14

Category : Business & Economics

ISBN : 9780761959502

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Book Description

Doing Research in Business and Management has been written to help students obtain a thorough understanding of the main methodological issues and options that are available to them as business and management researchers undertaking a masters or doctoral degree. Doing Research in Business and Management takes the reader through all of the important issues that need to be understood if a competent piece of research is to be produced at the masters or doctoral level in the business and management studies. The authors explain the interrelationship between the theoretical and empirical research as well as the differences between positivism and phenomenology. Not only do they put these concepts in context for the business and management student, but they go on to discuss how these different approaches are used in practice. Furthermore, the authors discuss the implications of quantitative and qualitative approaches to research. The book offers high-level advice on different numerical techniques available to researchers as well as different software packages that may be used for analyzing qualitative data. The book also discusses the use of the Internet to support research in masters and doctoral programs.