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001			86108
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008			160715s2016 gw | s |||| 0|eng d
020			_a9783319390147
040			_aES-MaUEC
050		4	_aQA279.6 _bF899 2016
082	0	4	_a006.3
245	1	0	_aFuzzy Statistical Decision-Making : _bTheory and Applications _cedited by Cengiz Kahraman, Özgür Kabak
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XII, 356 páginas) _b84 ilustraciones, 5 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aStudies in Fuzziness and Soft Computing _x1434-9922 _v343
505	0		_aPreface -- Fuzzy Statistical Decision Making -- Fuzzy Probability Theory I: Discrete Case -- Fuzzy Probability Theory II: Continuous Case -- On Fuzzy Bayesian Inference -- Fuzzy Central Tendency Measures -- Fuzzy Dispersion Measures -- Sufficiency, Completeness, and Unbiasedness based on Fuzzy Sample Space -- Fuzzy Confidence Regions -- Fuzzy Extensions of Confidence Intervals: Estimation for �, v2, and p -- Testing Fuzzy Hypotheses: A New p-value-based Approach -- Fuzzy Regression Analysis : An Actuarial Perspective -- Fuzzy Correlation and Fuzzy Non-Linear Regression Analysis -- Fuzzy Decision Trees -- Fuzzy Shewhart Control Charts -- Fuzzy EWMA and Fuzzy CUSUM Control Charts -- Linear Hypothesis Testing Based on Unbiased Fuzzy Estimators and Fuzzy Significance Level -- A Practical Application of Fuzzy Analysis of Variance in Agriculture -- A Survey of Fuzzy Data Mining Techniques.
520	3		_aThis book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, asignarmaterias , EBSPRINGER
650	0	7	_aInvestigación operativa _0 _2embne _9138674
650		7	_aToma de decisiones _0comprobar BNE19900995115 _2embne _9141176
700	1		_aKahraman, Cengiz _eeditor literario _0Local _997689
700	1		_aKabak, Özgür _eeditor literario _0Local _999551
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-39014-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319390147
907			_a.b12953866 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0
945			_aQA279.6 F899 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11596326 _z06-04-17
999			_c86108 _d86108 _x1