Probability- moment generating functions.

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Homework Help Overview

The discussion revolves around finding the moment generating function (MGF), expectation, and variance of a gamma-distributed random variable Y with parameters θ and n. The original poster presents the probability density function (PDF) and expresses difficulty in evaluating the integral for the MGF.

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants explore the integral definition of the MGF and suggest substitutions to simplify the evaluation. There are discussions about combining exponential factors and the implications of variable substitutions. Questions arise regarding the correctness of steps taken and the limits of integration.

Discussion Status

Participants are actively engaging with the problem, providing guidance on how to approach the integral and discussing the implications of certain substitutions. There is a focus on ensuring the conditions for convergence are met, and some participants are questioning the assumptions regarding the limits of t.

Contextual Notes

There is an emphasis on the requirement that t must be near 0 for the MGF to be valid, and participants are clarifying the implications of this condition on the evaluation of the integral.

C.E
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1. A random variable Y is called gamma([tex]\theta[/tex], n) for [tex]\theta[/tex]>0 and natural n if it takes positive values and takes the following PDF:

f(y)=[tex]\frac{1}{\theta (n-1)!}[/tex]([tex]\frac{y}{\theta}[/tex])[tex]^{n-1}[/tex] exp[tex]\frac{-y}{\theta}[/tex]

Show how to find the moment generating function, expectation and variance of Y.

3. I have not got very far I am stil stuck on finding the moment generating function.

I know it is given by the following:

[tex]\int_{0}^{\infty} \exp(ty)f(y) dy[/tex]

but I have no idea how to evaluate it and get the correct answer (can somebody please show me?)

The answer you should get is: G[tex]_{y}[/tex](t)=1/(1-t[tex]\theta[/tex])[tex]^{n}[/tex]


I think I will know how to find the expectation and variance once I have the moment generating function.
 
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Substitute [tex]u=\frac{(1-\theta t) y}{\theta}[/tex] .

(The restriction on t is that [tex]1-\theta t>0[/tex] .)
 
I do not see how that helps, could someone please elaborate?
 
Write down the integral you are trying to evaluate.

Don't just write "f(y)." Write down what f(y) is.

You now have two factors with e to a power. Combine them into one factor of e to a power, using properties of exponents.

Now make a u-substitution, the one I suggested, as in calc 1 or calc 2.

Write this out and show us how far you can get.
 
Ok this is as far as I keep getting:

[tex]\int_{0}^{\infty} e^{\frac{-y}{\theta}}e^{tx} {\frac{y^{n-1}}{(t\theta-1)^{n-1}}{\frac{1}{\theta(n-1)!} dy[/tex]

=[tex]\int_{0}^{\infty} e^{\frac{y(t\theta-1)}{\theta}}{\frac{y^{n-1}}{\theta^{n-1}}{\frac{1}{\theta(n-1)!}dy[/tex]

let u=[tex]{\frac{y(t\theta-1)}{\theta}[/tex]

Then du=[tex]{\frac{(t\theta-1)}{\theta}[/tex]dy

=[tex]\int_{0}^{\infty} {\frac{1}{(t\theta-1)(n-1)!}}{\frac{u^{n-1}}{(t\theta-1)^{n-1}}e^u du[/tex]
 
= [tex]\frac{1}{(t\theta-1)^n}[/tex] [tex]\int_{0}^{\infty} e^u \frac{u^{n-1}}{(n-1)!}[/tex]

Is this right so far? Is there some reason why [tex]\int_{0}^{\infty} e^u \frac{u^{n-1}}{(n-1)!}[/tex] should be one?
 
C.E, that's mostly pretty good!

Here is an important technical detail. The m.g.f. is defined for t near 0, so [tex]\theta t -1[/tex] is negative. This means that for the substitution you used, y=infinity would become u=-infinity. Thus, your integral with du should become from 0 to -infinity.

Now you can find [tex]\int u^{n-1} e^u\,du[/tex] using integration by parts. Or use a table of integrals. The first time you use IBP you obtain a formula involving [tex]\int u^{n-2} e^u\,du[/tex]. Then do IBP again and you get [tex]\int u^{n-3} e^u\,du[/tex]. Pretty soon you'll see what happens with the factorial.

Do the IBP with definite integrals, [tex]\int_a^b u\,dv=uv\bigr|_a^b-\int_a^b v\,du[/tex] so that you can take care of those "uv" terms at each step.
 
How do you know that the MGF is for t near to 0 (it does not say in the question)? I assume from the limits you told me it is for 0<t<1?
 
MGF is always for t near 0, because that's where you need it to find the mean and moments. M'(0), M''(0), etc.

[tex]\theta t -1<0[/tex] i.e. [tex]1-\theta t>0[/tex] will give you [tex]t<1/ \theta[/tex], and this last inequality includes t=0.

You need to use that condition to get your integral du from 0 to -infinity, and the -infinity will be used to get convergence of the improper integral.
 

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