Generating Functions
[13/54%]Let the random variable take only nonnegative integer values, and let , , be its generating function (that is, ). Does the generating function uniquely determine the distribution of the random variable ?
For any two independent random variables and , prove that .
Let be a nonnegative integer-valued random variable with generating function . Find the generating functions of the quantities:
;
;
.
Find the generating functions of random variables having:
a Bernoulli distribution with parameter ;
a binomial distribution with parameters and ;
a Poisson distribution with parameter ;
a geometric distribution with parameter .
Let be a nonnegative integer-valued random variable with generating function . In terms of , express the generating functions of the following sequences:
;
;
;
.
Let be a sequence of nonnegative integer-valued independent identically distributed random variables with generating function . Let be a positive integer-valued random variable, independent of , with generating function . Find the generating function of the sum of a random number of terms .
Find the distribution laws corresponding to the following generating functions:
;
;
;
, .
Let the random variable have generating function . Find the distribution of , if for every .
Prove that the function cannot be the generating function of a probability distribution.
Let the random variable take the values with probability each. Prove that if is composite, then can be represented as the sum of independent integer-valued random variables.
Let the random variable take the values 0 and 1 with probability each, and let take the values 0, 1, 2, and 3 with probabilities , , , and respectively. Prove that there does not exist a random variable , independent of , such that .
Solve problem 10.39 using generating functions.
Let be a sequence of independent identically distributed random variables with common distribution function . Let be a positive integer-valued random variable, independent of , with generating function . Prove that the distribution function of the random variable equals .