Large Deviations For A General-Class Of Random Vectors
The published version is located at http://www.jstor.org/stable/info/2243592
This paper proves large deviation theorems for a general class of random vectors taking values in Rd and in certain infinite dimensional spaces. The proofs are based on convexity methods. As an application, we give a new proof of the large deviation property of the empirical measures of finite state Markov chains (originally proved by M. Donsker and S. Varadhan). We also discuss a new notion of stochastic convergence, called exponential convergence, which is closely related to the large deviation results.
RS Ellis. "Large Deviations For A General-Class Of Random Vectors" Annals of Probability 12.1 (1984): 1-12.
Available at: http://works.bepress.com/richard_ellis/32
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