000 04239nam a22005895i 4500
001 978-0-8176-4987-6
003 DE-He213
005 20180115171442.0
007 cr nn 008mamaa
008 100907s2010 xxu| s |||| 0|eng d
020 _a9780817649876
_9978-0-8176-4987-6
024 7 _a10.1007/978-0-8176-4987-6
_2doi
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.2
_223
100 1 _aGupta, Arjun K.
_eauthor.
245 1 0 _aProbability and Statistical Models
_h[electronic resource] :
_bFoundations for Problems in Reliability and Financial Mathematics /
_cby Arjun K. Gupta, Wei-Bin Zeng, Yanhong Wu.
250 _aFirst.
264 1 _aBoston, MA :
_bBirkhäuser Boston :
_bImprint: Birkhäuser,
_c2010.
300 _aXII, 267 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPreliminaries -- 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.
520 _aWith 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.
650 0 _aMathematics.
650 0 _aEconomics, Mathematical.
650 0 _aMathematical models.
650 0 _aProbabilities.
650 0 _aStatistics.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 1 4 _aMathematics.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aMathematical Modeling and Industrial Mathematics.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
650 2 4 _aQuantitative Finance.
700 1 _aZeng, Wei-Bin.
_eauthor.
700 1 _aWu, Yanhong.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780817649869
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-8176-4987-6
912 _aZDB-2-SMA
999 _c370055
_d370055