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＜電子ブック＞
Probability and Statistical Models : Foundations for Problems in Reliability and Financial Mathematics / by Arjun K. Gupta, Wei-Bin Zeng, Yanhong Wu

版	1st ed. 2010.
出版者	(Boston, MA : Birkhäuser Boston : Imprint: Birkhäuser)
出版年	2010
大きさ	XII, 267 p : online resource
著者標目	*Gupta, Arjun K author Zeng, Wei-Bin author Wu, Yanhong author SpringerLink (Online service)
件　名	LCSH:Probabilities LCSH:Statistics  LCSH:Engineering mathematics LCSH:Engineering—Data processing LCSH:Mathematical models LCSH:Social sciences—Mathematics FREE:Probability Theory FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Mathematical and Computational Engineering Applications FREE:Mathematical Modeling and Industrial Mathematics FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Mathematics in Business, Economics and Finance
一般注記	Preliminaries -- Exponential Distribution -- Poisson Process -- Parametric Families of Lifetime Distributions -- Lifetime Distribution Classes -- Multivariate Lifetime Distributions -- Association and Dependence -- Renewal Theory -- Risk Theory -- Asset Pricing Theory -- Credit Risk Modeling With an emphasis on models and techniques, this textbook introduces many of the fundamental concepts of stochastic modeling that are now a vital component of almost every scientific investigation. These models form the basis of well-known parametric lifetime distributions such as exponential, Weibull, and gamma distributions, as well as change-point and mixture models. The authors also consider more general notions of non-parametric lifetime distribution classes. In particular, emphasis is placed on laying the foundation for solving problems in reliability, insurance, finance, and credit risk. Exercises and solutions to selected problems accompany each chapter in order to allow students to explore these foundations. The key subjects covered include: * Exponential distributions and the Poisson process * Parametric lifetime distributions * Non-parametric lifetime distribution classes * Multivariate exponential extensions * Association and dependence * Renewal theory * Problems in reliability, insurance, finance, and credit risk This work differs from traditional probability textbooks in a number of ways. Since no measure theory knowledge is necessary to understand the material and coverage of the central limit theorem and normal theory related topics has been omitted, the work may be used as a single-semester senior undergraduate or first-year graduate textbook as well as in a second course on probability modeling. Many of the chapters that examine central topics in applied probability can be read independently, allowing both instructors and readers extra flexibility in their use of the book. Probability and Statistical Models is for a wide audience including advanced undergraduate and beginning-level graduate students, researchers, and practitioners in mathematics, statistics, engineering, and economics HTTP:URL=https://doi.org/10.1007/978-0-8176-4987-6

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