Moment generating function for a random variable X is given by M(t)=$E[e^{tX}]$ for some −h < t < h.
Why does −h < t < h ?.
I am not able to understand the importance and meaning of parameter t in the definition of moment generating function. What does it signify?
I guess understanding this below question might help me in understanding the concept of parameter t in moment generating function. So please explain that also.
Let X be a random variable with mgf M(t), −h < t < h.
Prove that
(a) $P(X ≥ a) ≤ e^{−at}M(t) , 0 < t < h$
and that
(b) $P(X ≤ a) ≤ e^{−at}M(t) , − h < t < 0 $
(I am able to derive part(a) using markov's inequality but I dont understand for (a) to be true , why $ 0 < t < h$ ?)
Best Answer
There are at least two reasons for this.
Many r.v. Do not have an expected value because their PDFs are too large at infinity. In particular $E(e^X)$ may not be defined
All the useful information (namely the moments) is in the the derivatives at zero, and those exist as soon as you have a function defined in a neighborhood of zero.
Also, note that $M$ is a version of the Laplace transform of the pdf. (It is bilateral though) which exists typically for $t$ with a small real part.