000			03093cam a2200349Ii 4500
001			9781315140919
008			180706s2018 xx ob 001 0 eng d
020			_a9781315140919 _q(e-book : PDF)
020			_a9781351456159 _q(e-book: Mobi)
020			_z9780412246203 _q(hardback)
024	7		_a10.1201/9781315140919 _2doi
035			_a(OCoLC)1027755373
050		4	_aQA276.8 _bS558 2018
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.544
100	1		_aSilverman, Bernard. W., _eauthor. _913518
245	1	0	_aDensity Estimation for Statistics and Data Analysis / _cBernard. W. Silverman.
250			_aFirst edition.
264		1	_aBoca Raton, FL : _bCRC Press, _c2018.
300			_a1 online resource
505	0		_tchapter 1 Introduction / _rB.W. Silverman -- _tchapter 2 Survey of existing methods / _rB.W. Silverman -- _tchapter 3 The kernel method for univariate data / _rB.W. Silverman -- _tchapter 4 The kernel method for multivariate data / _rB.W. Silverman -- _tchapter 5 Three important methods / _rB.W. Silverman -- _tchapter 6 Density estimation in action / _rB.W. Silverman.
520	2		_a"Although there has been a surge of interest in density estimation in recent years, much of the published research has been concerned with purely technical matters with insufficient emphasis given to the technique's practical value. Furthermore, the subject has been rather inaccessible to the general statistician.The account presented in this book places emphasis on topics of methodological importance, in the hope that this will facilitate broader practical application of density estimation and also encourage research into relevant theoretical work. The book also provides an introduction to the subject for those with general interests in statistics. The important role of density estimation as a graphical technique is reflected by the inclusion of more than 50 graphs and figures throughout the text.Several contexts in which density estimation can be used are discussed, including the exploration and presentation of data, nonparametric discriminant analysis, cluster analysis, simulation and the bootstrap, bump hunting, projection pursuit, and the estimation of hazard rates and other quantities that depend on the density. This book includes general survey of methods available for density estimation. The Kernel method, both for univariate and multivariate data, is discussed in detail, with particular emphasis on ways of deciding how much to smooth and on computation aspects. Attention is also given to adaptive methods, which smooth to a greater degree in the tails of the distribution, and to methods based on the idea of penalized likelihood."--Provided by publisher.
650		0	_aMathematical statistics. _99597
650	0	4	_aARCHIVEnetBASE _913519
650	0	4	_aSCI-TECHnetBASE _912670
650	0	4	_aStatistical Theory & Methods _911140
650	0	4	_aSTATSnetBASE _913520
650	0	4	_aSTMnetBASE _912671
776	0	8	_iPrint version: _z9780412246203
856	4	0	_uhttps://www.taylorfrancis.com/books/9781315140919 _zClick here to view.
942			_cEBK
999			_c70465 _d70465