|
|
|
|
| LEADER |
03158nam a22005295i 4500 |
| 001 |
13757 |
| 003 |
DE-He213 |
| 005 |
20130727075741.0 |
| 007 |
cr nn 008mamaa |
| 008 |
130521s2013 xxu| s |||| 0|eng d |
| 020 |
# |
# |
|a 9781461471011
|9 978-1-4614-7101-1
|
| 024 |
7 |
# |
|a 10.1007/978-1-4614-7101-1
|2 doi
|
| 050 |
# |
4 |
|a QA273.A1-274.9
|
| 050 |
# |
4 |
|a QA274-274.9
|
| 072 |
# |
7 |
|a PBT
|2 bicssc
|
| 072 |
# |
7 |
|a PBWL
|2 bicssc
|
| 072 |
# |
7 |
|a MAT029000
|2 bisacsh
|
| 082 |
0 |
4 |
|a 519.2
|2 23
|
| 100 |
1 |
# |
|a Foss, Sergey.
|e author.
|
| 245 |
1 |
3 |
|a An Introduction to Heavy-Tailed and Subexponential Distributions
|c by Sergey Foss, Dmitry Korshunov, Stan Zachary.
|h [electronic resource] /
|
| 250 |
# |
# |
|a 2nd ed. 2013.
|
| 264 |
# |
1 |
|a New York, NY :
|b Springer New York :
|b Imprint: Springer,
|c 2013.
|
| 300 |
# |
# |
|a XI, 157 p. 2 illus.
|b online resource.
|
| 336 |
# |
# |
|a text
|b txt
|2 rdacontent
|
| 337 |
# |
# |
|a computer
|b c
|2 rdamedia
|
| 338 |
# |
# |
|a online resource
|b cr
|2 rdacarrier
|
| 347 |
# |
# |
|a text file
|b PDF
|2 rda
|
| 490 |
1 |
# |
|a Springer Series in Operations Research and Financial Engineering,
|x 1431-8598
|
| 505 |
0 |
# |
|a Preface -- Introduction -- Heavy- and long-tailed distributions -- Subexponential distributions -- Densities and local probabilities -- Maximum of random walks -- References -- Index.
|
| 520 |
# |
# |
|a Heavy-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. � One of the highlights of this new edition is that it includes problems at the end of each chapter. Chapter 5 is also updated to include interesting applications to queueing theory, risk, and branching processes. New results are presented in a simple, coherent and systematic way. Graduate students as well as modelers in the fields of finance, insurance, network science and environmental studies will find this book to be an essential reference.
|
| 650 |
# |
0 |
|a Mathematics.
|
| 650 |
# |
0 |
|a Distribution (Probability theory).
|
| 650 |
# |
0 |
|a Economics
|x Statistics.
|
| 650 |
1 |
4 |
|a Mathematics.
|
| 650 |
2 |
4 |
|a Probability Theory and Stochastic Processes.
|
| 650 |
2 |
4 |
|a Statistics for Business/Economics/Mathematical Finance/Insurance.
|
| 650 |
2 |
4 |
|a Statistical Physics, Dynamical Systems and Complexity.
|
| 700 |
1 |
# |
|a Korshunov, Dmitry.
|e author.
|
| 700 |
1 |
# |
|a Zachary, Stan.
|e author.
|
| 710 |
2 |
# |
|a SpringerLink (Online service)
|
| 773 |
0 |
# |
|t Springer eBooks
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9781461471004
|
| 830 |
# |
0 |
|a Springer Series in Operations Research and Financial Engineering,
|x 1431-8598
|
| 856 |
4 |
0 |
|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4614-7101-1
|
| 912 |
# |
# |
|a ZDB-2-SMA
|
| 950 |
# |
# |
|a Mathematics and Statistics (Springer-11649)
|