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Purely Game-theoretic Random Sequences: I. Strong Law of Large Numbers and Law of the Iterated Logarithm
- Source :
- Theory of Probability & Its Applications. 44:511-522
- Publication Year :
- 2000
- Publisher :
- Society for Industrial & Applied Mathematics (SIAM), 2000.
-
Abstract
- Random sequences are usually defined with respect to a probability distribution~$\bf P$ (a $\sigma$-additive set function, normed to one, defined over a $\sigma$-algebra) assuming Kolmogorov's axioms for probability theory. In this paper, without using this axiomatics, we give a definition of random (typical) sequences taking as primitive the notion of a martingale and using the principle of the excluded gambling strategy. In this purely game-theoretic framework, no probability distribution or, partially or fully specified, system of conditional probability distributions needs to be introduced. For these typical sequences, we prove direct algorithmic versions of Kolmogorov's strong law of large numbers (SLLN) and of the upper half of Kolmogorov's law of the iterated logarithm~(LIL).
- Subjects :
- Almost sure limit theorems
Statistics and Probability
Discrete mathematics
Law of total expectation
Probability axioms
Law of the iterated logarithm
Martingales
Typical sequences
Combinatorics
Algorithmic probability theory
Convergence of random variables
Probability theory
Probability distribution
Statistics, Probability and Uncertainty
Random variable
Algorithmically random sequence
Mathematics
Subjects
Details
- ISSN :
- 10957219 and 0040585X
- Volume :
- 44
- Database :
- OpenAIRE
- Journal :
- Theory of Probability & Its Applications
- Accession number :
- edsair.doi.dedup.....02a63e3820f9bdbe9ce0052525bea51d
- Full Text :
- https://doi.org/10.1137/s0040585x97977768