We study the empirical meaning of randomness with respect to a family of probability distributions Pθ, where θ is a real parameter, using algorithmic randomness theory. In the case when for a computable probability distribution Pθ an effectively strongly consistent estimate exists, we show that the Levin's a priory semicomputable semimeasure of the set of all Pθ-random sequences is positive if and only if the parameter θ is a computable real number. The different methods for generating "meaningful" Pθ-random sequences with noncomputable θ are discussed. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
V’yugin, V. (2007). On empirical meaning of randomness with respect to a real parameter. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4649 LNCS, pp. 387–396). Springer Verlag. https://doi.org/10.1007/978-3-540-74510-5_39
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