Abstract:
We obtain analogues of the well-known Chebyshev's exponential inequality
$\mathbf P(\xi \ge x)\le e^{-\Lambda^{(\xi)}(x)}$, $x>\mathbf E\,\xi$, for the distribution of a random variable $\xi$, where $\Lambda^{(\xi)}(x):=\sup_\lambda\{\lambda x- \log \mathbf E\,e^{\lambda \xi}\}$ is the large deviation rate function for $\xi$. Generalizations of this relation are established for multivariate random vectors $\xi$, for sums of the vectors, and for trajectories of random processes associated with such sums.
Keywords:Cramér condition, large deviation rate function, random walk, deviation functional, action functional, convex set, large deviations, large deviation principle, extended large deviation principle, inequalities for large deviations.