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Operator-Limit Distributions in Probability Theory
Written by two experts of multidimensional developments in a classic area of probability theory—the central limit theory. Features all essential tools to bring readers up to date in the field. Describes operator-selfdecomposable measures, operator-stable distributions and provides specialized techniques from probability theory.
Research Report
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Probability in Banach Spaces, 8: Proceedings of the Eighth International Conference
Probability limit theorems in infinite-dimensional spaces give conditions un der which convergence holds uniformly over an infinite class of sets or functions. Early results in this direction were the Glivenko-Cantelli, Kolmogorov-Smirnov and Donsker theorems for empirical distribution functions. Already in these cases there is convergence in Banach spaces that are not only infinite-dimensional but nonsep arable. But the theory in such spaces developed slowly until the late 1970's. Meanwhile, work on probability in separable Banach spaces, in relation with the geometry of those spaces, began in the 1950's and developed strongly in the 1960's and 70's. We have in mind here also work on sample...
