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"Every serious probabilist should, and doubtless will, possess a copy of this important work. Loeve is to be complimented on completing his Herculean task at a uniformly high level of elegance." ¯ Journal of the American Statistical Association.
"This is a very scholarly book in the best tradition of analysis. Nothing else of this type exists for the benefit of the serious student of the subject and it is safe to predict that it will remain a standard compendium for many years to come." ¯ S. Vajda in Zentralblatt fur Mathematik.
In the decades following its 1963 publication, this volume served as the standard advanced text in probability theory. Geared toward graduate students and professionals in the field of probability and statistics, the treatment offers extensive introductory material and is suitable for an undergraduate course in probability theory. The first four chapters cover notions of measure theory plus general concepts and tools of probability theory. Subsequent chapters explore sums of independent random variables, the central limit problem, conditioning, independence and dependence, ergodic theorems, and second order properties. The final two chapters examine foundations, martingales, and decomposability as well as Markov processes.
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"Every serious probabilist should, and doubtless will, possess a copy of this important work. Loeve is to be complimented on completing his Herculean task at a uniformly high level of elegance." ¯ Journal of the American Statistical Association.
"This is a very scholarly book in the best tradition of analysis. Nothing else of this type exists for the benefit of the serious student of the subject and it is safe to predict that it will remain a standard compendium for many years to come." ¯ S. Vajda in Zentralblatt fur Mathematik.
In the decades following its 1963 publication, this volume served as the standard advanced text in probability theory. Geared toward graduate students and professionals in the field of probability and statistics, the treatment offers extensive introductory material and is suitable for an undergraduate course in probability theory. The first four chapters cover notions of measure theory plus general concepts and tools of probability theory. Subsequent chapters explore sums of independent random variables, the central limit problem, conditioning, independence and dependence, ergodic theorems, and second order properties. The final two chapters examine foundations, martingales, and decomposability as well as Markov processes.
