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A graduate course in probability /
A Graduate Course in Probability.
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Academic Press,
1967.
|
| Colección: | Probability and mathematical statistics ;
2. |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Tucker, Howard G. | |
| 245 | 1 | 2 | |a A graduate course in probability / |c Howard G. Tucker. |
| 264 | 1 | |a New York : |b Academic Press, |c 1967. | |
| 300 | |a 1 online resource (xiii, 273 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; a series of monographs and textbooks ; |v 2 | |
| 504 | |a Includes bibliographical references (page 270). | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Front Cover; A Graduate Course in Probability; Copyright Page; Dedication; Preface; Table of Contents; CHAPTER 1. Probability Spaces; 1.1 Sigma Fields; 1.2 Probability Measures; 1.3 Random Variables; CHAPTER 2. Probability Distributions; 2.1. Univariate Distribution Functions; 2.2. Multivariate Distribution Functions; 2.3. Distribution of a Set of Infinitely Many Random Variables; 2.4. Expectation; 2.5. Characteristic Functions; CHAPTER 3. Stochastic Independence; 3.1. Independent Events; 3.2. Independent Random Variables; 3.3. The Zero-One Law; CHAPTER 4. Basic Limiting Operations. | |
| 505 | 8 | |a 4.1. Convergence of Distribution Functions4.2. The Continuity Theorem; 4.3. Refinements of the Continuity Theorem for Nonvanishing Characteristic Functions; 4.4. The Four Types of Convergence: Almost Sure, in Law, in Probability, and in rth Mean; CHAPTER 5. Strong Limit Theorems for Independent Random Variables; 5.1. Almost Sure Convergence of Series of Independent Random Variables; 5.2. Proof that Convergence in Law of a Series of Independent Random Variables Implies Almost Sure Convergence; 5.3. The Strong Law of Large Numbers; 5.4. The Glivenko-Cantelli Theorem. | |
| 505 | 8 | |a 5.5. Inequalities for the Law of the Iterated Logarithm5.6. The Law of the Iterated Logarithm; CHAPTER 6. The Central Limit Theorem; 6.1. Infinitely Divisible Distributions; 6.2. Canonical Representation of Infinitely Divisible Characteristic Functions; 6.3 Convergence of Infinitely Divisible Distribution Functions; 6.4. Infinitesimal Systems of Random Variables; 6.5. The General Limit Theorem for Sequences of Sums of Independent Random Variables; 6.6. Convergence to the Normal and Poisson Distributions; CHAPTER 7. Conditional Expectation and Martingale Theory; 7.1. Conditional Expectation. | |
| 505 | 8 | |a 7.2. Martingales and Submartingales7.3. Martingale and Submartingale Convergence Theorems; 7.4. Brownian Motion; CHAPTER 8. An Introduction to Stochastic Processes and, in Particular, Brownian Motion; 8.1 Probability Measures over Function Spaces; 8.2 Separable Stochastic Processes; 8.3 Continuity and Nonrectifiability of Almost All Sample Functions of Separable Brownian Motion; 8.4. The Law of the Iterated Logarithm for Separable Brownian Motion; Suggested Reading; Index. | |
| 520 | |a A Graduate Course in Probability. | ||
| 546 | |a English. | ||
| 650 | 0 | |a Probabilities. | |
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| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
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| 776 | 0 | 8 | |i Print version: |a Tucker, Howard G. |t Graduate course in probability |z 0127026460 |w (DLC) 66030820 |w (OCoLC)528562 |
| 830 | 0 | |a Probability and mathematical statistics ; |v 2. | |
| 856 | 4 | 0 | |u https://sciencedirect.uam.elogim.com/science/book/9780127026466 |z Texto completo |