000 | 03835nam a22005655i 4500 | ||
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001 | 978-1-4614-8471-4 | ||
003 | DE-He213 | ||
005 | 20140220082501.0 | ||
007 | cr nn 008mamaa | ||
008 | 131216s2014 xxu| s |||| 0|eng d | ||
020 |
_a9781461484714 _9978-1-4614-8471-4 |
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024 | 7 |
_a10.1007/978-1-4614-8471-4 _2doi |
|
050 | 4 | _aQA402-402.37 | |
050 | 4 | _aT57.6-57.97 | |
072 | 7 |
_aKJT _2bicssc |
|
072 | 7 |
_aKJM _2bicssc |
|
072 | 7 |
_aBUS049000 _2bisacsh |
|
072 | 7 |
_aBUS042000 _2bisacsh |
|
082 | 0 | 4 |
_a519.6 _223 |
100 | 1 |
_aZabarankin, Michael. _eauthor. |
|
245 | 1 | 0 |
_aStatistical Decision Problems _h[electronic resource] : _bSelected Concepts and Portfolio Safeguard Case Studies / _cby Michael Zabarankin, Stan Uryasev. |
264 | 1 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2014. |
|
300 |
_aXIV, 249 p. 9 illus., 4 illus. in color. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSpringer Optimization and Its Applications, _x1931-6828 ; _v85 |
|
505 | 0 | _a1. Random Variables -- 2. Deviation, Risk, and Error Measures -- 3. Probabilistic Inequalities -- 4. Maximum Likelihood Method -- 5. Entropy Maximization -- 6. Regression Models -- 7. Classification -- 8. Statistical Decision Models with Risk and Deviation -- 9. Portfolio Safeguard Case Studies -- Index -- References. | |
520 | _aStatistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications. | ||
650 | 0 | _aMathematics. | |
650 | 0 | _aData mining. | |
650 | 0 | _aMathematical optimization. | |
650 | 0 | _aDistribution (Probability theory). | |
650 | 0 | _aOperations research. | |
650 | 1 | 4 | _aMathematics. |
650 | 2 | 4 | _aOperations Research, Management Science. |
650 | 2 | 4 | _aProbability Theory and Stochastic Processes. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aOptimization. |
650 | 2 | 4 | _aOperation Research/Decision Theory. |
700 | 1 |
_aUryasev, Stan. _eauthor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9781461484707 |
830 | 0 |
_aSpringer Optimization and Its Applications, _x1931-6828 ; _v85 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4614-8471-4 |
912 | _aZDB-2-SMA | ||
999 |
_c92178 _d92178 |