000			03207nam a2200373 i 4500
001			CR9781139014830
003			UkCbUP
005			20240301142634.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			110214s2014||||enk o ||1 0|eng|d
020			_a9781139014830 (ebook)
020			_z9780521498845 (hardback)
020			_z9780521738415 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA273.67 _b.D84 2014
082	0	0	_a519.2 _223
100	1		_aDudley, R. M. _q(Richard M.), _eauthor.
245	1	0	_aUniform central limit theorems / _cR.M. Dudley, Massachusetts Institute of Technology.
250			_aSecond edition.
264		1	_aCambridge : _bCambridge University Press, _c2014.
300			_a1 online resource (xii, 472 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aCambridge studies in advanced mathematics ; _v142
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	8		_aMachine generated contents note: 1. Donsker's theorem and inequalities; 2. Gaussian processes; sample continuity; 3. Definition of Donsker classes; 4. Vapnik-Cervonenkis combinatorics; 5. Measurability; 6. Limit theorems for VC-type classes; 7. Metric entropy with bracketing; 8. Approximation of functions and sets; 9. Two samples and the bootstrap; 10. Uniform and universal limit theorems; 11. Classes too large to be Donsker; Appendix A. Differentiating under an integral sign; Appendix B. Multinomial distributions; Appendix C. Measures on nonseparable metric spaces; Appendix D. An extension of Lusin's theorem; Appendix E. Bochner and Pettis integrals; Appendix F. Non-existence of some linear forms; Appendix G. Separation of analytic sets; Appendix H. Young-Orlicz spaces; Appendix I. Versions of isonormal processes.
520			_aIn this new edition of a classic work on empirical processes the author, an acknowledged expert, gives a thorough treatment of the subject with the addition of several proved theorems not included in the first edition, including the Bretagnolle-Massart theorem giving constants in the Komlos-Major-Tusnady rate of convergence for the classical empirical process, Massart's form of the Dvoretzky-Kiefer-Wolfowitz inequality with precise constant, Talagrand's generic chaining approach to boundedness of Gaussian processes, a characterization of uniform Glivenko-Cantelli classes of functions, Giné and Zinn's characterization of uniform Donsker classes, and the Bousquet-Koltchinskii-Panchenko theorem that the convex hull of a uniform Donsker class is uniform Donsker. The book will be an essential reference for mathematicians working in infinite-dimensional central limit theorems, mathematical statisticians, and computer scientists working in computer learning theory. Problems are included at the end of each chapter so the book can also be used as an advanced text.
650		0	_aCentral limit theorem.
776	0	8	_iPrint version: _z9780521498845
830		0	_aCambridge studies in advanced mathematics ; _v142.
856	4	0	_uhttps://doi.org/10.1017/CBO9781139014830
999			_c8958 _d8958