Weibull ModelsJohn Wiley & Sons, 28 січ. 2004 р. - 416 стор. A comprehensive perspective on Weibull models The literature on Weibull models is vast, disjointed, andscattered across many different journals. Weibull Models is acomprehensive guide that integrates all the different facets ofWeibull models in a single volume. This book will be of great help to practitioners in reliabilityand other disciplines in the context of modeling data sets usingWeibull models. For researchers interested in these modelingtechniques, exercises at the end of each chapter define potentialtopics for future research. Organized into seven distinct parts, Weibull Models: * Covers model analysis, parameter estimation, model validation,and application * Serves as both a handbook and a research monograph. As ahandbook, it classifies the different models and presents theirproperties. As a research monograph, it unifies the literature andpresents the results in an integrated manner * Intertwines theory and application * Focuses on model identification prior to model parameterestimation * Discusses the usefulness of the Weibull Probability plot (WPP)in the model selection to model a given data set * Highlights the use of Weibull models in reliability theory Filled with in-depth analysis, Weibull Models pulls together themost relevant information on this topic to give everyone fromreliability engineers to applied statisticians involved withreliability and survival analysis a clear look at what Weibullmodels can offer. |
Зміст
PART B BASIC WEIBULL MODEL | 43 |
PART C TYPES I AND II MODELS | 103 |
PART D TYPE III MODELS | 157 |
PART E TYPES IV TO VII MODELS | 221 |
PART F WEIBULL MODELING OF DATA | 281 |
PART G APPLICATIONS IN RELIABILITY | 301 |
References | 348 |
377 | |
Інші видання - Показати все
Загальні терміни та фрази
Analysis Applications approach appropriate assume asymptote Bayesian called censored Chapter characterization competing risk component Compute conditional consider continuous cost Data Set deals decreasing defined denote density function depends derived determine discussed distribution function Edition Exercise exponential failed failure Figure first fit follows function is given graphical hazard function increasing indicated interval inverse Weibull involves Jiang Journal linear maintenance manufacturing maximum likelihood mean method mixture model model parameters model selection moments multivariate Murthy needs Note obtained operation Parameter Estimation possible probability problem procedure proposed random variable reduces reliability renewal result sample scale Second shape parameter similar standard Weibull model Statistical Step straight line stress subpopulations Table Theory tion transformation two-parameter Weibull Type warranty Weibull distribution Weibull mixture WPP plot yields
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Maintenance, Replacement, and Reliability: Theory and Applications Andrew K.S. Jardine,Albert H.C. Tsang Обмежений попередній перегляд - 2005 |
Precedence-Type Tests and Applications Narayanaswamy Balakrishnan,H. K. Tony Ng Обмежений попередній перегляд - 2006 |