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Strong Approximations in Probability and Statistics.
Strong Approximations in Probability and Statistics.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York : Budapest :
Academic Press ; Akad�emiai Kiad�o,
�1981.
|
| Colección: | Probability and mathematical statistics.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 003 | OCoLC | ||
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| 082 | 0 | 4 | |a 519.2 |
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| 100 | 1 | |a Cs�org�o, M. | |
| 245 | 1 | 0 | |a Strong Approximations in Probability and Statistics. |
| 260 | |a New York : |b Academic Press ; |a Budapest : |b Akad�emiai Kiad�o, |c �1981. | ||
| 300 | |a 1 online resource (287 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Probability and mathematical statistics | |
| 588 | 0 | |a Print version record. | |
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a Strong Approximations in Probability and Statistics. | ||
| 506 | |3 Use copy |f Restrictions unspecified |2 star |5 MiAaHDL | ||
| 533 | |a Electronic reproduction. |b [Place of publication not identified] : |c HathiTrust Digital Library, |d 2010. |5 MiAaHDL | ||
| 538 | |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |u http://purl.oclc.org/DLF/benchrepro0212 |5 MiAaHDL | ||
| 583 | 1 | |a digitized |c 2010 |h HathiTrust Digital Library |l committed to preserve |2 pda |5 MiAaHDL | |
| 505 | 0 | |a Front Cover; Strong Approximations in Probability and Statistics; Copyright Page; Table of Contents; Preface; Introduction; Chapter 1. Wiener and some Related Gaussian Processes; 1.0 On the notion of a Wiener process; 1.1 Definition and existence of a Wiener process; 1.2 How big are the increments of a Wiener process?; 1.3 The law of iterated logarithm for the Wiener process; 1.4 Brownian bridges; 1.5 The distributions of some functional of the Wiener and Brownian bridge processes; 1.6 The modulus of non-differentiability of the Wiener process | |
| 505 | 8 | |a 2.1 A proof of Donsker's theorem with Skorohod's embedding scheme2.2 The strong invariance principle appears; 2.3 The stochastic Geyser problem as a lower limit to the strong invariance problem; 2.4 The longest runs of pure heads and the stochastic Geyser problem; 2.5 Improving the upper limit; 2.6 The best rates emerge; Supplementary remarks; Chapter 3. A Study of Partial Sums with the Help of Strong Approximation Methods; 3.0 Introduction; 3.1 How big are the increments of partial sums of I.I.D.R.V. when the moment generating function exists? | |
| 505 | 8 | |a 3.2 How big are the increments of partial sums of I.I.D.R.V. when the moment generating function does not exist?3.3 How small are the increments of partial sums of I.I.D.R.V.?; 3.4 A summary; Supplementary remarks; Chapter 4. Strong Approximations of Empirical Processes by Gaussian Processes; 4.1 Some classical results; 4.2 Why should the empirical process behave like a Brownian bridge?; 4.3 The first strong approximations of the empirical process; 4.4 Best strong approximations of the empirical process; 4.5 Strong approximation of the quantile process; Supplementary remarks | |
| 505 | 8 | |a Chapter 5. A Study of Empirical and Quantile Processes with the Help of Strong Approximation Methods5.0 Introduction; 5.1 The law of iterated logarithm for the empirical process; 5.2 The distance between the empirical and the quantile processes; 5.3 The law of iterated logarithm for the quantile process; 5.4 Asymptotic distribution results for some classical functionals of the empirical process; 5.5 Asymptotic distribution results for some classical functionals of the quantile process | |
| 650 | 0 | |a Approximation theory. | |
| 650 | 0 | |a Stochastic approximation. | |
| 650 | 0 | |a Invariants. | |
| 650 | 0 | |a Probabilities. | |
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 2 | |a Probability |0 (DNLM)D011336 | |
| 650 | 6 | |a Th�eorie de l'approximation. |0 (CaQQLa)201-0021344 | |
| 650 | 6 | |a Probabilit�es. |0 (CaQQLa)201-0011592 | |
| 650 | 6 | |a Statistique math�ematique. |0 (CaQQLa)201-0002592 | |
| 650 | 6 | |a Approximation stochastique. |0 (CaQQLa)201-0075368 | |
| 650 | 6 | |a Invariants. |0 (CaQQLa)201-0005695 | |
| 650 | 7 | |a probability. |2 aat |0 (CStmoGRI)aat300055653 | |
| 650 | 7 | |a MATHEMATICS |x Applied. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a Probabilities |2 fast |0 (OCoLC)fst01077737 | |
| 650 | 7 | |a Mathematical statistics |2 fast |0 (OCoLC)fst01012127 | |
| 650 | 7 | |a Stochastic approximation |2 fast |0 (OCoLC)fst01133501 | |
| 650 | 7 | |a Approximation theory |2 fast |0 (OCoLC)fst00811829 | |
| 650 | 7 | |a Invariants |2 fast |0 (OCoLC)fst00977982 | |
| 650 | 1 | 7 | |a Waarschijnlijkheid (statistiek) |2 gtt |
| 650 | 1 | 7 | |a Statistiek. |2 gtt |
| 653 | 0 | |a 11030 |a stochastic processes |a 21030 |a approximation | |
| 653 | 0 | |a Stochastic approximation | |
| 700 | 1 | |a R�ev�esz, P. | |
| 700 | 1 | |a Birnbaum, Z. W. | |
| 700 | 1 | |a Lukacs, E. | |
| 776 | 0 | 8 | |i Print version: |a Cs�orgo, M. |t Strong Approximations in Probability and Statistics. |d Burlington : Elsevier Science, �2014 |z 9780121985400 |
| 830 | 0 | |a Probability and mathematical statistics. | |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780121985400 |z Texto completo |