000 03405nam a22005295i 4500
001 978-1-4419-9473-8
003 DE-He213
005 20140220083729.0
007 cr nn 008mamaa
008 110524s2011 xxu| s |||| 0|eng d
020 _a9781441994738
_9978-1-4419-9473-8
024 7 _a10.1007/978-1-4419-9473-8
_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 _aFoss, Sergey.
_eauthor.
245 1 3 _aAn Introduction to Heavy-Tailed and Subexponential Distributions
_h[electronic resource] /
_cby Sergey Foss, Dmitry Korshunov, Stan Zachary.
250 _a1.
264 1 _aNew York, NY :
_bSpringer New York,
_c2011.
300 _aIX, 123p. 1 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598 ;
_v38
505 0 _aPreface -- Introduction -- Heavy- and long-tailed distributions -- Subexponential distributions.- Densities and local probabilities -- Maximum of random walks -- References -- Index.
520 _aHeavy-tailed probability distributions are an important component in the modeling of many stochastic systems. They are frequently used to accurately model inputs and outputs of computer and data networks and service facilities such as call centers. They are an essential for describing risk processes in finance and also for insurance premia pricing, and such distributions occur naturally in models of epidemiological spread. The class includes distributions with power law tails such as the Pareto, as well as the lognormal and certain Weibull distributions.  This monograph defines the classes of long-tailed and subexponential distributions in one dimension and provides a complete and comprehensive description of their properties. New results are presented in a simple, coherent and systematic way. This leads to a comprehensive exposition of tail properties of sums of independent random variables whose distributions belong to the long-tailed and subexponential class. The book includes a discussion of and references to contemporary areas of applications and also contains preliminary mathematical material which makes the book self contained. Modelers in the fields of finance, insurance, network science and environmental studies will find this book to be an essential reference.
650 0 _aMathematics.
650 0 _aDistribution (Probability theory).
650 0 _aEconomics
_xStatistics.
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 _aStatistical Physics, Dynamical Systems and Complexity.
700 1 _aKorshunov, Dmitry.
_eauthor.
700 1 _aZachary, Stan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441994721
830 0 _aSpringer Series in Operations Research and Financial Engineering,
_x1431-8598 ;
_v38
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4419-9473-8
912 _aZDB-2-SMA
999 _c106058
_d106058