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AuthorChung, Kai Lai. author
TitleLectures from Markov Processes to Brownian Motion [electronic resource] / by Kai Lai Chung
ImprintNew York, NY : Springer New York : Imprint: Springer, 1982
Connect tohttp://dx.doi.org/10.1007/978-1-4757-1776-1
Descript VIII, 242 p. 5 illus. online resource

SUMMARY

This book evolved from several stacks of lecture notes written over a decade and given in classes at slightly varying levels. In transforming the overยญ lapping material into a book, I aimed at presenting some of the best features of the subject with a minimum of prerequisities and technicalities. (Needless to say, one man's technicality is another's professionalism. ) But a text frozen in print does not allow for the latitude of the classroom; and the tendency to expand becomes harder to curb without the constraints of time and audience. The result is that this volume contains more topics and details than I had intended, but I hope the forest is still visible with the trees. The book begins at the beginning with the Markov property, followed quickly by the introduction of option al times and martingales. These three topics in the discrete parameter setting are fully discussed in my book A Course In Probability Theory (second edition, Academic Press, 1974). The latter will be referred to throughout this book as the Course, and may be considered as a general background; its specific use is limited to the mateยญ rial on discrete parameter martingale theory cited in ยง 1. 4. Apart from this and some dispensable references to Markov chains as examples, the book is self-contained


CONTENT

1 Markov Process -- 2 Basic Properties -- 3 Hunt Process -- 4 Brownian Motion -- 5 Potential Developments


Mathematics Probabilities Mathematics Probability Theory and Stochastic Processes



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