000			03025nam a22004335i 4500
001			978-3-642-10473-2
003			DE-He213
005			20140220083741.0
007			cr nn 008mamaa
008			110824s2011 gw | s |||| 0|eng d
020			_a9783642104732 _9978-3-642-10473-2
024	7		_a10.1007/978-3-642-10473-2 _2doi
050		4	_aQA276-280
072		7	_aPBT _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.5 _223
100	1		_aPuntanen, Simo. _eauthor.
245	1	0	_aMatrix Tricks for Linear Statistical Models _h[electronic resource] : _bOur Personal Top Twenty / _cby Simo Puntanen, George P. H. Styan, Jarkko Isotalo.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011.
300			_aXX, 486p. 78 illus., 2 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aIntroduction -- Easy Column Space Tricks -- Easy Projector Tricks -- Easy Correlation Tricks -- Generalized Inverses in a Nutshell -- Rank of the Partitioned Matrix and the Matrix Product -- Rank Cancellation Rule -- Sum of Orthogonal Projector -- Minimizing cov(y - Fx) -- BLUE -- General Solution to AYB = C -- Invariance with Respect to the Choice of Generalized Inverse -- Block-Diagonalization and the Schur Complement -- Nonnegative Definiteness of a Partitioned Matrix -- The Matrix M -- Disjointness of Column Spaces -- Full Rank Decomposition -- Eigenvalue Decomposition -- Singular Value Decomposition -- The Cauchy-Schwarz Inequality -- Notation -- References -- Author Index -- Subject Index.
520			_aIn teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple “tricks” which simplify and clarify the treatment of a problem—both for the student and for the professor. Of course, the concept of a trick is not uniquely defined—by a trick we simply mean here a useful important handy result. In this book we collect together our Top Twenty favourite matrix tricks for linear statistical models.
650		0	_aStatistics.
650		0	_aMathematical statistics.
650	1	4	_aStatistics.
650	2	4	_aStatistical Theory and Methods.
700	1		_aStyan, George P. H. _eauthor.
700	1		_aIsotalo, Jarkko. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642104725
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-10473-2
912			_aZDB-2-SMA
999			_c106725 _d106725