Bernstein inequalities (probability theory)

For independent centered variables $X_i\le b$ and $v={\sum }_i\mathbb{E}{X}_i^2$,

Suppose independent centered sub-exponential random variables satisfy $\log \mathbb{E}{e}^{\lambda X_i}\le v_i{\lambda }^2/(2(1-b|\lambda |))$ for $|\lambda |<1/b$, and put $v={\sum }_i{v}_i$. Independence adds the log moment-generating functions. The Chernoff bound with $\lambda =t/(v+bt)$ gives the displayed two-sided tail. If each variable has common scale $K$, one may take $v_i\le C{K}^2$ and $b\le CK$, giving $\mathbb{P}(|n^{-1}{\sum }_i{X}_i|>t)\le 2e^{-cn\min \{t^2/K^2,t/K\}}$. This form of Bernstein's inequality allows unbounded variables with factorial moment control, including the centered square of a sub-Gaussian random variable.