000 02337nam a22003498i 4500
001 CR9781316576533
003 UkCbUP
005 20200124160335.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 150903s2016||||nyu o ||1 0|eng|d
020 _a9781316576533 (ebook)
020 _z9781107149892 (hardback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 4 _aQA276.4
_b.E47 2016
082 0 4 _a519.50285
_223
100 1 _aEfron, Bradley,
_eauthor.
245 1 0 _aComputer age statistical inference :
_balgorithms, evidence, and data science /
_cBradley Efron, Trevor Hastie.
264 1 _aNew York :
_bCambridge University Press,
_c2016.
300 _a1 online resource (xix, 475 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aInstitute of Mathematical Statistics monographs ;
_v5
500 _aTitle from publisher's bibliographic system (viewed on 04 Jul 2016).
520 _aThe twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
650 0 _aMathematical statistics
_xData processing.
700 1 _aHastie, Trevor,
_eauthor.
776 0 8 _iPrint version:
_z9781107149892
830 0 _aInstitute of Mathematical Statistics monographs ;
_v5.
856 4 0 _uhttps://doi.org/10.1017/CBO9781316576533
999 _c522932
_d522930