(a) Let X and Y be real random variables such that E[f(X)]=E[f(Y)] for every compactly supported continuous function f. Show that X and Y have the same law.
(b) Given a real random variable Z, let φZ(s)=E(eisZ) be its characteristic function. Prove the identity
∬g(εs)f(x)e−isxφZ(s)dsdx=∫g^(t)E[f(Z−εt)]dt
for real ε>0, where is f is continuous and compactly supported, and where g is a Lebesgue integrable function such that g^ is also Lebesgue integrable, where
g^(t)=∫g(x)eitxdx
is its Fourier transform. Use the above identity to derive a formula for E[f(Z)] in terms of φZ, and recover the fact that φZ determines the law of Z uniquely.
(c) Let X and Y be bounded random variables such that E(Xn)=E(Yn) for every positive integer n. Show that X and Y have the same law.
(d) The Laplace transform ψZ(s) of a non-negative random variable Z is defined by the formula
ψZ(s)=E(e−sZ)
for s⩾0. Let X and Y be (possibly unbounded) non-negative random variables such that ψX(s)=ψY(s) for all s⩾0. Show that X and Y have the same law.
(e) Let
f(x;k)=1{x>0}k!1xke−x
where k is a non-negative integer and 1{x>0} is the indicator function of the interval (0,+∞).
Given non-negative integers k1,…,kn, suppose that the random variables X1,…,Xn are independent with Xi having density function f(⋅;ki). Find the density of the random variable X1+⋯+Xn.