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Mathematical statistics --- Failure time data analysis. --- Survival analysis (Biometry). --- Failure time data analysis --- Survival analysis (Biometry) --- 368.01 --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Analysis, Failure time data --- Data analysis, Failure time --- Biometry --- Failure analysis (Engineering) --- Competing risks

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Mathematical statistics --- Failure time data analysis --- Reliability (Engineering) --- Temps entre défaillances, Analyse des --- Fiabilité --- Survival analysis (Biometry) --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Competing risks --- Failure time data analysis. --- Survival analysis (Biometry). --- Temps entre défaillances, Analyse des --- Fiabilité

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This is the definitive reference containing all of the background guidance, typical ranges, details of recommended test specifications, case studies and regulations covering the environmental requirements on designers and manufacturers of electrical and electromechanical equipment worldwide.The recent introduction of the European EMC directive is just one aspect of the requirements placed upon manufacturers and designers of electrical equipment. There are numerous national and international standards and specifications that describe the application environment in which equipment must f

Electric apparatus and appliances --- Electric machinery --- Electronic apparatus and appliances --- Environmental engineering --- Environmental testing --- Failure time data analysis --- Testing. --- Standards. --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Mathematical statistics --- Competing risks --- Survival analysis (Biometry) --- Environment testing --- Testing --- Environmental control --- Environmental effects --- Environmental stresses --- Engineering --- Environmental health --- Environmental protection --- Pollution --- Sustainable engineering

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"The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival Analysis presents a comprehensive overview of the fundamental approaches in the area of frailty models. The book extensively explores how univariate frailty models can represent unobserved heterogeneity. It also emphasizes correlated frailty models as extensions of univariate and shared frailty models. The author analyzes similarities and differences between frailty and copula models; discusses problems related to frailty models, such as tests for homogeneity; and describes parametric and semiparametric models using both frequentist and Bayesian approaches. He also shows how to apply the models to real data using the statistical packages of R, SAS, and Stata. The appendix provides the technical mathematical results used throughout. Written in nontechnical terms accessible to nonspecialists, this book explains the basic ideas in frailty modeling and statistical techniques, with a focus on real-world data application and interpretation of the results. By applying several models to the same data, it allows for the comparison of their advantages and limitations under varying model assumptions. The book also employs simulations to analyze the finite sample size performance of the models."--Publisher's description.

Mathematical statistics --- Failure time data analysis --- Survival analysis (Biometry) --- Mortality --- Demography --- Mathematics --- Mathematical models --- #SBIB:314H160 --- #SBIB:303H520 --- #SBIB:314H220 --- Historical demography --- Social sciences --- Population --- Vital statistics --- Mortality, Law of --- Death --- Death (Biology) --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Competing risks --- Bevolkingsstudies: onderzoeks- en analysemethoden --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Mortaliteit: algemeen --- Failure time data analysis - Mathematics --- Survival analysis (Biometry) - Mathematics --- Mortality - Mathematical models --- Demography - Mathematics

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Survival analysis, the analysis of failure time data, is a rapid developing area and a number of books on the topic have been published in last twenty-five years. However, all of these books deal with right-censored failure time data, not the analysis of interval-censored failure time data. Interval-censored data include right-censored data as a special case and occur in many fields. The analysis of interval-censored data is much more difficult than that of right-censored data because the censoring mechanism that yields interval censoring is more complicated than that for right censoring. This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. A number of inference approaches are discussed in the book, including the maximum likelihood, estimating equations, sieve maximum likelihood, and conditional likelihood. One major difference between the analyses of right- and interval-censored data is that the theory of counting processes, which is responsible for substantial advances in the theory and development of modern statistical methods for right-censored data, is not applicable to interval-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. In addition, Bayesian methods and the analysis of interval-censored data with informative interval censoring are considered as well as the analysis of interval-censored recurrent event, or panel count, data. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions. It can also be used as a text for a graduate course in statistics or biostatistics that assume a basic knowledge of probability and statistics. Jianguo (Tony) Sun is a professor at the Department of Statistics of the University of Missouri-Columbia. He has developed novel statistical methods for the analysis of interval-censored failure time data and panel count data over the last fifteen years.

Failure time data analysis. --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Mathematical statistics --- Competing risks --- Survival analysis (Biometry) --- Distribution (Probability theory. --- Statistics. --- Probability Theory and Stochastic Processes. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Probabilities. --- Statistics . --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk