grandes-ecoles 2017 QII.B.1

grandes-ecoles · France · centrale-maths1__psi Moment generating functions Concentration inequality via MGF and Markov's inequality (Chernoff method)

The interval $I$ and the function $\varphi_{X}$ are defined as in question I.A.4. We suppose that $X$ satisfies $(C_{\tau})$ for some $\tau > 0$, is not almost surely constant, and $a > E(X)$.
Show that, for $n$ in $\mathbb{N}^{*}$ and $t$ in $I \cap \mathbb{R}^{+}$ $$E\left(\mathrm{e}^{tS_{n}}\right) = \left(\varphi_{X}(t)\right)^{n}, \quad P\left(S_{n} \geqslant na\right) \leqslant \frac{\varphi_{X}(t)^{n}}{\mathrm{e}^{nta}}$$

The interval $I$ and the function $\varphi_{X}$ are defined as in question I.A.4. We suppose that $X$ satisfies $(C_{\tau})$ for some $\tau > 0$, is not almost surely constant, and $a > E(X)$.

Show that, for $n$ in $\mathbb{N}^{*}$ and $t$ in $I \cap \mathbb{R}^{+}$
$$E\left(\mathrm{e}^{tS_{n}}\right) = \left(\varphi_{X}(t)\right)^{n}, \quad P\left(S_{n} \geqslant na\right) \leqslant \frac{\varphi_{X}(t)^{n}}{\mathrm{e}^{nta}}$$

Paper Questions

QI.A.1 QI.A.2 QI.A.3 QI.A.4 QI.B.1 QI.B.2 QI.C.1 QI.C.2 QI.C.3 QII.A.1 QII.A.2 QII.A.3 QII.B.1 QII.B.2 QII.C.1 QII.C.2 QII.C.3