We assume that $X$ and $Y$ are two independent discrete real-valued random variables with strictly positive values admitting moments of all orders. We denote $R _ { X }$ (respectively $R _ { Y }$) the radius of convergence (assumed strictly positive) associated with the function $M _ { X }$ (respectively $M _ { Y }$). Show that the random variable $X + Y$ admits moments of all orders and that $$\forall | t | < \min \left( R _ { X } , R _ { Y } \right) , \quad M _ { X + Y } ( t ) = M _ { X } ( t ) \times M _ { Y } ( t )$$
We assume that $X$ and $Y$ are two independent discrete real-valued random variables with strictly positive values admitting moments of all orders. We denote $R _ { X }$ (respectively $R _ { Y }$) the radius of convergence (assumed strictly positive) associated with the function $M _ { X }$ (respectively $M _ { Y }$).
Show that the random variable $X + Y$ admits moments of all orders and that
$$\forall | t | < \min \left( R _ { X } , R _ { Y } \right) , \quad M _ { X + Y } ( t ) = M _ { X } ( t ) \times M _ { Y } ( t )$$