The laws of large numbers [electronic resource]
The Laws of Large Numbers.
Saved in:
| Online Access: |
Full Text (via ScienceDirect) |
|---|---|
| Main Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York :
Academic Press,
1968 [©1967]
|
| Series: | Probability and mathematical statistics ;
v. 4. |
| Subjects: |
MARC
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| 100 | 1 | |a Révész, Pál. |0 http://id.loc.gov/authorities/names/n50045224 |1 http://isni.org/isni/0000000109981982. | |
| 245 | 1 | 4 | |a The laws of large numbers |h [electronic resource] |
| 260 | |a New York : |b Academic Press, |c 1968 [©1967] | ||
| 300 | |a 1 online resource (176 pages) | ||
| 336 | |a text |b txt |2 rdacontent. | ||
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| 490 | 1 | |a Probability and mathematical statistics, |v 4. | |
| 504 | |a Includes bibliographical references (pages 169-173) | ||
| 505 | 0 | |a Front Cover; The Laws of Large Numbers; Copyright Page; Table of Contents; INTRODUCTION; CHAPTER 0. MATHEMATICAL BACKGROUND; 0.1. Measure theory; 0.2. Probability theory; 0.3. Stochastic processes; 0.4. Hubert and Banach spaces; 0.5. Ergodic theory; 0.6. Orthogonal series; CHAPTER 1. DEFINITIONS AND GENERALITIES; 1.1. The different kinds of the laws of large numbers; 1.2. General theorems; CHAPTER 2. INDEPENDENT RANDOM VARIABLES; 2.1. Inequalities; 2.2. The three series theorem; 2.3. What are the possible limits?; 2.4. Convergence in mean; 2.5. Weak laws. | |
| 505 | 8 | |a 4.3. The estimation of the covariance functionCHAPTER 5. SUBSEQUENCES OF SEQUENCES OF RANDOM VARIABLES; 5.1. A conjecture of H. Steinhaus; 5.2. Subsequences of stationary sequences; 5.3. Subsequences of special orthogonal sequences; CHAPTER 6. SYMMETRICALLY DEPENDENT RANDOM VARIABLES AND THEIR GENERALIZATIONS; 6.1. Symmetrically dependent random variables; 6.2. Quasi-independent events; 6.3. Quasi-multiplicative systems; CHAPTER 7. MARKOV CHAINS; 7.1. Homogeneous Markov chains; 7.2. Non-homogeneous Markov chains; 7.3. The law of the iterated logarithm. | |
| 505 | 8 | |a CHAPTER 8. WEAKLY DEPENDENT RANDOM VARIABLES 8.1. A general theorem on centered random variables; 8.2. Mixing; CHAPTER 9. INDEPENDENT RANDOM VARIABLES TAKING VALUES IN AN ABSTRACT SPACE; 9.1. Independent random variables taking values in a Hilbert space; 9.2. Independent random variables taking values ina Banach space; CHAPTER 10. SUM OF A RANDOM NUMBER OF INDEPENDENTRANDOM VARIABLES; CHAPTER 11. APPLICATIONS; 11.1. Applications in number theory; 11.2. Applications in statistics; 11.3. Applications in information theory; REFERENCES; AUTHOR INDEX. | |
| 520 | |a The Laws of Large Numbers. | ||
| 588 | 0 | |a Print version record. | |
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| 776 | 0 | 8 | |i Print version: |a Révész, Pál. |t Laws of large numbers. |d New York, Academic Press, 1968 [©1967] |w (DLC) 68026629 |w (OCoLC)448249. |
| 830 | 0 | |a Probability and mathematical statistics ; |v v. 4. |0 http://id.loc.gov/authorities/names/n42019721. | |
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