We are given a probability space $( \Omega , \mathcal { A } , \mathbb { P } )$. 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 $Y$ admits a finite expectation, that is, if the series $\sum n ^ { m } P ( Y = n )$ converges. We then call the moment of order $m$ of $Y$ the real number $$\mathbb { E } \left( Y ^ { m } \right) = \sum _ { n = 0 } ^ { \infty } n ^ { m } \mathbb { P } ( Y = n )$$ Show that if $Y : \Omega \rightarrow \mathbb { N }$ is a random variable associated with a generating function $G _ { Y }$ of radius strictly greater than 1, then $Y$ admits a finite moment of all orders.
We are given a probability space $( \Omega , \mathcal { A } , \mathbb { P } )$. 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 $Y$ admits a finite expectation, that is, if the series $\sum n ^ { m } P ( Y = n )$ converges. We then call the moment of order $m$ of $Y$ the real number
$$\mathbb { E } \left( Y ^ { m } \right) = \sum _ { n = 0 } ^ { \infty } n ^ { m } \mathbb { P } ( Y = n )$$
Show that if $Y : \Omega \rightarrow \mathbb { N }$ is a random variable associated with a generating function $G _ { Y }$ of radius strictly greater than 1, then $Y$ admits a finite moment of all orders.