By K. R. Parthasarathy
Having been out of print for over 10 years, the AMS is overjoyed to carry this vintage quantity again to the mathematical neighborhood. With this nice exposition, the writer provides a cohesive account of the speculation of likelihood measures on whole metric areas (which he perspectives instead method of the overall thought of stochastic processes). After a basic description of the fundamentals of topology at the set of measures, he discusses regularity, tightness, and perfectness of measures, houses of sampling distributions, and metrizability and compactness theorems. subsequent, he describes mathematics houses of chance measures on metric teams and in the neighborhood compact abelian teams. coated intimately are notions similar to decomposability, countless divisibility, idempotence, and their relevance to restrict theorems for "sums" of infinitesimal random variables. The ebook concludes with quite a few effects on the topic of restrict theorems for likelihood measures on Hilbert areas and at the areas $C[0,1]$. The Mathematical experiences reviews in regards to the unique variation of this booklet are as actual this present day as they have been in 1967. It is still a compelling paintings and a valuable source for studying in regards to the concept of likelihood measures. the amount is acceptable for graduate scholars and researchers attracted to chance and stochastic methods and could make an excellent supplementary studying or self sufficient examine textual content.
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