000			02036 a2200265 4500
005			20180219104000.0
008			180131b xxu||||| |||| 00| 0 eng d
020			_a9780521861601
040			_cIIT Kanpur
041			_aeng
082			_a519.2 _bSch97c
100			_aSchweder, Tore
245			_aConfidence, likelihood, probability _bstatistical inference with confidence distributions _cTore Schweder and Nils Lid Hjort
260			_bCambridge University Press _c2016 _aNew York
300			_axx, 500
440			_aCambridge series in statistical and probabilistic mathematics
490			_a/ edited by Z. Ghahramani ; no.41
520			_aThis lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits, they lead to optimal combinations of confidence from different sources of information, and they can make complex models amenable to objective and indeed prior-free analysis for less subjectively inclined statisticians. The generous mixture of theory, illustrations, applications and exercises is suitable for statisticians at all levels of experience, as well as for data-oriented scientists. Some confidence distributions are less dispersed than their competitors. This concept leads to a theory of risk functions and comparisons for distributions of confidence. Neyman–Pearson type theorems leading to optimal confidence are developed and richly illustrated. Exact and optimal confidence distribution is the gold standard for inferred epistemic distributions. Confidence distributions and likelihood functions are intertwined, allowing prior distributions to be made part of the likelihood. Meta-analysis in likelihood terms is developed and taken beyond traditional methods, suiting it in particular to combining information across diverse data sources.
650			_aMathematical statistics
650			_aProbability
650			_aApplied statistics
650			_aObserved confidence levels (Statistics)
700			_aHjort, Nils Lid
942			_cBK
999			_c558494 _d558494