We are given a probability space $( \Omega , \mathcal { A } , \mathbb { P } )$. We define $H_k(X) = X(X-1)\cdots(X-k+1)$ for $k \in \mathbb{N}^*$ and $H_0(X)=1$. Let $m$ be a strictly positive integer. We say that a random variable $Y : \Omega \rightarrow \mathbb { N }$ admits a finite moment of order $m$ if the series $\sum n ^ { m } P ( Y = n )$ converges, and $\mathbb { E } \left( Y ^ { m } \right) = \sum _ { n = 0 } ^ { \infty } n ^ { m } \mathbb { P } ( Y = n )$. Let $Y : \Omega \rightarrow \mathbb { N }$ be a random variable admitting a finite moment of all orders. IV.B.1) Show that the generating function $G _ { Y }$ is of class $C ^ { \infty }$ on $[ - 1,1 ]$. IV.B.2) Express $G _ { Y } ^ { ( k ) } ( 1 )$ using the polynomials $H _ { k } ( X )$ and the random variable $Y$. IV.B.3) Does the generating function $G _ { Y }$ necessarily have a radius of convergence strictly greater than 1? One may use the power series $\sum \mathrm { e } ^ { - \sqrt { n } } x ^ { n }$.
We are given a probability space $( \Omega , \mathcal { A } , \mathbb { P } )$. We define $H_k(X) = X(X-1)\cdots(X-k+1)$ for $k \in \mathbb{N}^*$ and $H_0(X)=1$. Let $m$ be a strictly positive integer. We say that a random variable $Y : \Omega \rightarrow \mathbb { N }$ admits a finite moment of order $m$ if the series $\sum n ^ { m } P ( Y = n )$ converges, and $\mathbb { E } \left( Y ^ { m } \right) = \sum _ { n = 0 } ^ { \infty } n ^ { m } \mathbb { P } ( Y = n )$.
Let $Y : \Omega \rightarrow \mathbb { N }$ be a random variable admitting a finite moment of all orders.
IV.B.1) Show that the generating function $G _ { Y }$ is of class $C ^ { \infty }$ on $[ - 1,1 ]$.
IV.B.2) Express $G _ { Y } ^ { ( k ) } ( 1 )$ using the polynomials $H _ { k } ( X )$ and the random variable $Y$.
IV.B.3) Does the generating function $G _ { Y }$ necessarily have a radius of convergence strictly greater than 1? One may use the power series $\sum \mathrm { e } ^ { - \sqrt { n } } x ^ { n }$.