000			01628nam a2200277Ia 4500
003			OSt
005			20250731163848.0
008			220909b |||||||| |||| 00| 0 eng d
020			_a9781461484707
037			_cTextual
040			_aCSL _beng _cCSL
041			_aeng
084			_aB28 Q4 _qCSL
100			_aZabarankin Michael _eauthor
245		0	_aStatistical decision problems _b: selected concepts and portfolio safeguard case studies
260			_aNew York : _bSpringer, _c2014.
300			_axiv, 249p. _b: ill.
500			_aReferences 241-244p.; Index 245-249p.
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.
650			_a Maximum likelihood methods _9817044
650			_a Regression models _9817045
650			_aProbabilistic inequalities _9817046
700			_aUsyasev, Stan _eco-author _9817047
942			_hB28 Q4 _cTEXL _2CC _n0
999			_c14671 _d14671