000			03485cam a2200505M 4500
001			9780429157158
003			FlBoTFG
005			20251030122225.0
006			m d
007			cr |||||||||||
008			221208s2023 flu o ||| 0 eng d
040			_aOCoLC-P _beng _cOCoLC-P
020			_a0429157150 _q(electronic bk.)
020			_a9780429157158 _q(electronic bk.)
020			_a9780429543968 _q(electronic bk. : Mobipocket)
020			_a0429543964 _q(electronic bk. : Mobipocket)
020			_a9781482242751 _q(electronic bk. : PDF)
020			_a1482242753 _q(electronic bk. : PDF)
020			_a9780429529269 _q(electronic bk. : EPUB)
020			_a0429529260 _q(electronic bk. : EPUB)
024	7		_a10.1201/9780429157158 _2doi
035			_a(OCoLC)1353734542
035			_a(OCoLC-P)1353734542
050		4	_aQA276.4
072		7	_aMAT _x029000 _2bisacsh
072		7	_aPBT _2bicssc
100	1		_aSzékely, Gábor J., _d1947- _eauthor. _1https://isni.org/isni/0000000110623154 _992345
245	1	0	_aENERGY OF DATA AND DISTANCE CORRELATION _h[electronic resource].
260			_aBOCA RATON : _bCHAPMAN & HALL CRC, _c2023.
300			_a1 online resource
490	0		_aChapman & Hall/CRC monographs on statistics & applied probability
520			_aEnergy distance is a statistical distance between the distributions of random vectors, which characterizes equality of distributions. The name energy derives from Newton's gravitational potential energy, and there is an elegant relation to the notion of potential energy between statistical observations. Energy statistics are functions of distances between statistical observations in metric spaces. The authors hope this book will spark the interest of most statisticians who so far have not explored E-statistics and would like to apply these new methods using R. The Energy of Data and Distance Correlation is intended for teachers and students looking for dedicated material on energy statistics, but can serve as a supplement to a wide range of courses and areas, such as Monte Carlo methods, U-statistics or V-statistics, measures of multivariate dependence, goodness-of-fit tests, nonparametric methods and distance based methods. E-statistics provides powerful methods to deal with problems in multivariate inference and analysis. Methods are implemented in R, and readers can immediately apply them using the freely available energy package for R. The proposed book will provide an overview of the existing state-of-the-art in development of energy statistics and an overview of applications. Background and literature review is valuable for anyone considering further research or application in energy statistics.
588			_aOCLC-licensed vendor bibliographic record.
650		7	_aMATHEMATICS / Probability & Statistics / General _2bisacsh _963965
650		0	_aMathematical statistics _xData processing. _964750
650		0	_aStatistics _xData processing. _965438
650		0	_aR (Computer program language) _xStatistical methods. _992346
650		0	_aForce and energy. _966844
700	1		_aRizzo, Maria L., _eauthor. _1https://isni.org/isni/0000000115661221 _992347
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9780429157158
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942			_cE-Books
999			_c67311 _d67311