000			01574nam a2200253 a 4500
001			vtls000101691
003			IIMC
005			20221117193445.0
008			140626 2010 000 0 eng d
020			_a9781420093438
039		9	_y201406262004 _zVLOAD
082	0	4	_a510 _bAIT
100	1		_aAitkin, Murray _92793656
245	1		_aStatistical inference : _b an integrated bayesian / likelihood approach / _cMurray Aitkin
260			_aBoca Raton : _bCRC Press, _c2010
300			_axvii, 236p. 23cm.
440			_aMonographs on statistics and applied probability ; _v 116 _92793657
504			_aAfter an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It presents Bayesian versions of one- and two-sample t-tests, along with the corresponding normal variance tests. The author then thoroughly discusses the use of the multinomial model and no informative Dirichlet priors in model-free or nonparametric Bayesian survey analysis, before covering normal regression and analysis of variance. In the chapter on binomial and multinomial data, he gives alternatives, based on Bayesian analyses, to current frequents nonparametric methods. The text concludes with new goodness-of-fit methods for assessing parametric models and a discussion of two-level variance component models and finite mixtures.
650		0	_aMathematical statistics. _92793658
901			_a132850~~~C
903			_a132850~~~C
904			_a<Mathematical statistics.>
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999			_c948010 _d948010