What is the Moment Generating Function for the Distribution f(x) = 2x?

In summary, the homework statement is that to determine the moment generating function of a function, you use the Maclaurin series for the variable.
  • #1
cse63146
452
0

Homework Statement



Let f(x) = 2x 0<x<1

a) Determing the Moment Generating function M(t) of X
b) Use the MGT to determine all moments about the origin
c) Give the 3rd central moment called the skewness

Homework Equations





The Attempt at a Solution



a) [tex]\int^1_0 e^{tx}2x dx = \frac{2xe^{tx}}{t} - \int^1_0 e^{tx}2 dx
= \frac{2}{t}(xe^{tx} - e^t + 1)[/tex]

b)

[tex]E\left(X^n\right)=M^{(n)}(0)=\left.\frac{\mathrm {d}^n M_(t)}{\mathrm{d}t^n}\right|_{t=0}[/tex]

[tex]E\left(X^n\right)=M^{(n)}(0)=\left.\frac{\mathrm {d}^n \frac{2}{t}(xe^{tx} - e^t + 1)}{\mathrm{d}t^n}\right|_{t=0}[/tex]

Is that what I'm supposed to do for part b)?
 
Last edited:
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  • #2
(a) can't be right because the x should have been integrated out. It's easy to correct what you did wrong.

(b) is the correct method, OR it might be easier to express the answer to (a) as a known power series, depending on what it really turns out to be.
 
  • #3
Sorry, I'm not sure what you meant by " x should have been integrated out". Does that mean that I did the integral wrong?
 
  • #4
cse63146 said:
Sorry, I'm not sure what you meant by " x should have been integrated out".

I meant [tex]\int_a^b F(x,t)\,dx[/tex] depends on t only, not x. Your (a) has an x in it so there is an (easy to fix) error.
 
  • #5
Is the 'x' you're referring to - [tex]\frac{2xe^{tx}}{t}[/tex]. If so, I'm not sure how to get rid of it.

Sorry if I'm being difficult
 
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  • #6
Sorry if I'm being difficult

You're not being difficult.

For integration by parts, you tried

[tex]\int_a^b u\,dv=uv-\int_a^b v\,du[/tex]

but the correct formula

[tex]\int_a^b u\,dv=uv\bigr|_a^b-\int_a^b v\,du[/tex]
 
  • #7
In [tex]uv|^1_0,[/tex] the [tex]|^1_0[/tex] applies to both u and v, or just v?
 
  • #8
Both u and v
 
  • #9
Once I use [tex]uv|^1_0[/tex], I get this:

[tex]\frac{2e^t}{t} - \frac{2}{t}(e^t -1) = \frac{2}{t}[/tex].

So when I apply I take the nth derivative I get:

[tex] - \frac{2}{nt^n}[/tex]

but I can't evaluate it at 0 since the denominator = 0. Did I make a mistake somewhere?
 
  • #10
Double check your integration to see if it should be [tex]\frac{2e^t}{t} - \frac{2}{t^2}(e^t -1)=\frac{2te^t-2e^t+2}{t^2}[/tex]

This is made continuous at t=0, which you can verify by l'Hopital or by substituting the Maclaurin series for e^t. In fact, I think it might be easier to use Maclaurin series for e^t to find the moments as well, but I admit I didn't try differentiating.
 
  • #11
Can I leave it like this (cause I don't know how the to find the nth derivative of a quotient)

[tex]\frac{d^n \frac{2te^t-2e^t+2}{t^2}}{dt}[/tex]
 
  • #12
I would prefer to substitute the power series for e^t, simplify, then get the derivatives at 0 from that, to see if there is a pattern to the nth moment.
 

1. What is a moment generating function?

A moment generating function (MGF) is a function used in probability theory and statistics to characterize the distribution of a random variable. It is defined as the expected value of e^tx, where t is a real number and x is the random variable.

2. How is a moment generating function related to moments?

The n-th moment of a distribution can be calculated using the n-th derivative of the moment generating function evaluated at t=0. This means that the moment generating function contains information about the moments of a distribution.

3. Can the moment generating function uniquely determine a distribution?

Yes, under certain conditions, the moment generating function can uniquely determine a distribution. This is known as the moment problem. However, there are cases where different distributions can have the same moment generating function, so it is not always the case.

4. What is the purpose of using a moment generating function?

Moment generating functions are useful in probability and statistics because they allow us to easily find the moments of a distribution, which can provide important information about the distribution. They are also used in the derivation of many commonly used distributions and in statistical inference.

5. How do you calculate the moment generating function of a distribution?

The process for calculating the moment generating function of a distribution depends on the specific distribution. In some cases, it is a simple formula, while in others it may require integration or other mathematical techniques. The moment generating function can also be derived from the probability density function of a distribution.

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