In probability theory, the probability generating function of a discrete random variable is a power series representation (the generating function) of the probability mass function of the random variable.
Probability generating functions are often employed for their succinct description of the sequence of probabilities Pr(X = i) in the probability mass function for a random variable X, and to make available the well-developed theory of power series with non-negative coefficients.
If X is a discrete random variable taking values x in the non-negative integers {0,1, ...}, then the probability generating function of X is defined as [1] where
Note that the subscripted notations
are often used to emphasize that these pertain to a particular random variable
The power series converges absolutely at least for all complex numbers
; the radius of convergence being often larger.
If X = (X1,...,Xd) is a discrete random variable taking values (x1,...,xd) in the d-dimensional non-negative integer lattice {0,1, ...}d, then the probability generating function of X is defined as where p is the probability mass function of X.
The power series converges absolutely at least for all complex vectors
Probability generating functions obey all the rules of power series with non-negative coefficients.
So the radius of convergence of any probability generating function must be at least 1, by Abel's theorem for power series with non-negative coefficients.
The following properties allow the derivation of various basic quantities related to
: Probability generating functions are particularly useful for dealing with functions of independent random variables.
For example: The probability generating function is an example of a generating function of a sequence: see also formal power series.
It is equivalent to, and sometimes called, the z-transform of the probability mass function.
The probability generating function is also equivalent to the factorial moment generating function, which as
can also be considered for continuous and other random variables.