000			02566nam a22003858i 4500
001			CR9780511546822
003			UkCbUP
005			20200124160235.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			090508s2006||||enk o ||1 0|eng|d
020			_a9780511546822 (ebook)
020			_z9780521868426 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA279 _b.W53 2006
082	0	0	_a519.5 _222
100	1		_aWichura, Michael J. _q(Michael John), _eauthor.
245	1	4	_aThe coordinate-free approach to linear models / _cMichael J. Wichura.
264		1	_aCambridge : _bCambridge University Press, _c2006.
300			_a1 online resource (xiii, 199 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aCambridge series on statistical and probabilistic mathematics ; _v19
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aTopics in linear algebra -- Random vectors -- Gauss-Markov estimation -- Normal theory: estimation -- Normal theory: testing -- Analysis of covariance -- Missing observations.
520			_aThis book is about the coordinate-free, or geometric, approach to the theory of linear models; more precisely, Model I ANOVA and linear regression models with non-random predictors in a finite-dimensional setting. This approach is more insightful, more elegant, more direct, and simpler than the more common matrix approach to linear regression, analysis of variance, and analysis of covariance models in statistics. The book discusses the intuition behind and optimal properties of various methods of estimating and testing hypotheses about unknown parameters in the models. Topics covered range from linear algebra, such as inner product spaces, orthogonal projections, book orthogonal spaces, Tjur experimental designs, basic distribution theory, the geometric version of the Gauss-Markov theorem, optimal and non-optimal properties of Gauss-Markov, Bayes, and shrinkage estimators under assumption of normality, the optimal properties of F-test, and the analysis of covariance and missing observations.
650		0	_aLinear models (Statistics)
650		0	_aAnalysis of variance.
650		0	_aRegression analysis.
650		0	_aAnalysis of covariance.
776	0	8	_iPrint version: _z9780521868426
830		0	_aCambridge series on statistical and probabilistic mathematics ; _v19.
856	4	0	_uhttps://doi.org/10.1017/CBO9780511546822
999			_c517976 _d517974