The laws of large numbers.

The Laws of Large Numbers.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: R�ev�esz, P�al
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, Academic Press, 1968 [�1967]
Colección:Probability and mathematical statistics ; 4.
Temas:
Law of large numbers.
Mathematical statistics.
Probabilities.
Probability
Statistique math�ematique.
Probabilit�es.
Loi des grands nombres.
probability.
Wahrscheinlichkeitstheorie
Probabilidade (Estatistica)
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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
  • 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
  • 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

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