000 03814nam a22005175i 4500
001 978-3-319-39014-7
003 DE-He213
005 20180206183019.0
007 cr nn 008mamaa
008 160715s2016 gw | s |||| 0|eng d
020 _a9783319390147
_9978-3-319-39014-7
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aFuzzy Statistical Decision-Making
_h[recurso electrónico] :
_bTheory and Applications /
_cedited by Cengiz Kahraman, Özgür Kabak.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXII, 356 p. 84 illus., 5 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 _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 µ, ?2, 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 _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.
650 0 _aEngineering.
650 0 _aOperations research.
650 0 _aDecision making.
650 0 _aStatistics.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aOperation Research/Decision Theory.
700 1 _aKahraman, Cengiz.
_eeditor.
700 1 _aKabak, Özgür.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319390123
830 0 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v343
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://dx.doi.org/10.1007/978-3-319-39014-7
912 _aZDB-2-ENG
942 _cLIBRO_ELEC
999 _c226381
_d226381