Probability and Statistical Models [recurso electrónico] : Foundations for Problems in Reliability and Financial Mathematics / by Arjun K. Gupta, Wei-Bin Zeng, Yanhong Wu.

Por: Gupta, Arjun K [author.]Colaborador(es): Zeng, Wei-Bin [author.] | Wu, Yanhong [author.] | SpringerLink (Online service)Tipo de material: TextoTextoEditor: Boston, MA : Birkhäuser Boston : Imprint: Birkhäuser, 2010Edición: FirstDescripción: XII, 267p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9780817649876Tema(s): Mathematics | Finance | Distribution (Probability theory) | Economics -- Statistics | Engineering mathematics | Mathematics | Probability Theory and Stochastic Processes | Statistics for Business/Economics/Mathematical Finance/Insurance | Appl.Mathematics/Computational Methods of Engineering | Mathematical Modeling and Industrial Mathematics | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences | Quantitative FinanceFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 519.2 Clasificación LoC:QA273.A1-274.9QA274-274.9Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer eBooksResumen: 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.
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Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos QA273 .A1-274.9 (Browse shelf(Abre debajo)) 1 No para préstamo 370434-2001

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.

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