000			03383nam a2200529Ii 4500
001			9780429057489
003			FlBoTFG
005			20220724194420.0
006			m o d
007			cr
008			190122t20182019fluab ob 001 0 eng d
020			_a9780429057489(e-book : PDF)
035			_a(OCoLC)1079055581
040			_aFlBoTFG _cFlBoTFG _erda
050		4	_aQA276
072		7	_aMAT _x029000 _2bisacsh
072		7	_aPBT _2bicscc
082	0	4	_a519.5/7 _223
100	1		_aRussell, Kenneth G., _eauthor.
245	1	0	_aDesign of Experiments for Generalized Linear Models / _cby Kenneth G. Russell.
250			_aFirst edition.
264		1	_aBoca Raton, FL : _bChapman and Hall/CRC, _c[2018].
264		4	_c©2019.
300			_a1 online resource (240 pages) : _b51 illustrations, text file, PDF.
336			_atext _2rdacontent
337			_acomputer _2rdamedia
338			_aonline resource _2rdacarrier
490	1		_aChapman & Hall/CRC Interdisciplinary Statistics
504			_aIncludes bibliographical references and index.
505	0	0	_tGeneralized Linear Models Background Material The Theory Underlying Design The Binomial Distribution The Poisson Distribution Several Other Distributions Bayesian experimental design.
520	3		_aGeneralized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM, little information is available on how to collect the data that are to be analysed in this way. This is the first book focusing specifically on the design of experiments for GLMs. Much of the research literature on this topic is at a high mathematical level, and without any information on computation. This book explains the motivation behind various techniques, reduces the difficulty of the mathematics, or moves it to one side if it cannot be avoided, and gives examples of how to write and run computer programs using R. Features The generalisation of the linear model to GLMs Background mathematics, and the use of constrained optimisation in R Coverage of the theory behind the optimality of a design Individual chapters on designs for data that have Binomial or Poisson distributions Bayesian experimental design An online resource contains R programs used in the book This book is aimed at readers who have done elementary differentiation and understand minimal matrix algebra, and have familiarity with R. It equips professional statisticians to read the research literature. Nonstatisticians will be able to design their own experiments by following the examples and using the programs provided.
530			_aAlso available in print format.
650		7	_abinomial distribution. _2bisacsh
650		7	_alinear mixed models. _2bisacsh
650		7	_alinear models. _2bisacsh
650		7	_amixture experiments. _2bisacsh
650		7	_aPoisson distribution. _2bisacsh
650		7	_aR software. _2bisacsh
650		0	_aLinear models (Statistics)
650		0	_aExperimental design.
655		0	_aElectronic books.
710	2		_aTaylor and Francis.
776	0	8	_iPrint version: _z9781498773133
830		0	_aChapman & Hall/CRC Interdisciplinary Statistics.
856	4	0	_uhttps://www.taylorfrancis.com/books/9780429057489 _zClick here to view
942			_2lcc _cEBK
999			_c17358 _d17358