Abstract
We consider a continuous time version of Cramer’s theorem with non-negative summands \( S_t = \tfrac{1} {t}\sum\nolimits_{i:\tau _i \leqslant t} {\xi _i ,} {\text{ }}t \to \infty \), where (τi, ξi)i≥1 is a sequence of random variables such that tS t is a random process with independent increments.
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Klebaner, F., Liptser, R. (2008). Cramer’s Theorem for Nonnegative Multivariate Point Processes with Independent Increments. In: Chow, PL., Yin, G., Mordukhovich, B. (eds) Topics in Stochastic Analysis and Nonparametric Estimation. The IMA Volumes in Mathematics and its Applications, vol 145. Springer, New York, NY. https://doi.org/10.1007/978-0-387-75111-5_2
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DOI: https://doi.org/10.1007/978-0-387-75111-5_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-75110-8
Online ISBN: 978-0-387-75111-5
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