Finding the joint moment generating function given the joint PDF

In summary, the problem is that the integral is non-elementary and needs to be written in terms of the error function. However, there is a shortcut that can be used if the integral is simplified first.
  • #1
stripes
266
0

Homework Statement



attachment.php?attachmentid=68177&stc=1&d=1396257940.jpg


Homework Equations





The Attempt at a Solution



attachment.php?attachmentid=68178&stc=1&d=1396258056.jpg


The problem is the integral is non-elementary, so now what? Part (b) follows trivially from part (a). But is there some kind of shortcut I have to take, because no matter what substitution I do, the integral needs to be written in terms of the error function, which is out of the scope of this course. Any hints would be great. Thanks.
 

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  • #2
Try something.
Try integrating over x for example.
You will be surprised.
 
  • #3
it seems something will just "vanish" but i can't find what, mainly because there is always the factor of e^x in there that gets in the way. I realize that it looks like a bivariate normal distribution though...
 
  • #4
Try integrating on x, as a start.
Since the integration spans [-Inf, +Inf], you will end up with a definite integral.
Alternatively, you might re-use known results on Laplace transforms.
See for example:

http://planetmath.org/laplacetransformofagaussianfunction

Proving what you find there is not difficult and could be interesting.

Other hint: 2bx + x² = (x+b)² - b²
 
  • #5
stripes said:

Homework Statement



attachment.php?attachmentid=68177&stc=1&d=1396257940.jpg


Homework Equations





The Attempt at a Solution



attachment.php?attachmentid=68178&stc=1&d=1396258056.jpg


The problem is the integral is non-elementary, so now what? Part (b) follows trivially from part (a). But is there some kind of shortcut I have to take, because no matter what substitution I do, the integral needs to be written in terms of the error function, which is out of the scope of this course. Any hints would be great. Thanks.

Do the x-integration first; it has the form
[tex] G(t,y) = \int_{-\infty}^{\infty} e^{-y} e^{tx} e^{-(x-y)^2/2}/\sqrt{2 \pi} \, dx [/tex]
Basically, this is a standard Gaussian integral, and it can be done in closed form because the integration limits are ##\pm \infty##. See. eg., http://en.wikipedia.org/wiki/Gaussian_integral .
 
  • #6
to me, e^-(x-y)^2 looks like a gaussian integral. but with the extra e^(tx), it no longer looks like a "standard" gaussian integral. of course i can see that because the limits are +/- infinity, that the x integration is just going to give root pi, or 1 or something stupid easy, but I'm not terribly familiar with WHAT the actual volume is under the 3d graph of a standard gaussian, let alone a gaussian with an extra e^(tx) in it...
 
  • #7
wolfram gives

http://www4b.wolframalpha.com/Calculate/MSP/MSP11611geaf4ba3b24ad0800005cf7hi62g6gf6c5i?MSPStoreType=image/gif&s=23&w=230.&h=49.

as the integral wrt x. i can't "see" that. but it looks like it follows from maajdl's suggestion...
 
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  • #8
stripes said:
to me, e^-(x-y)^2 looks like a gaussian integral. but with the extra e^(tx), it no longer looks like a "standard" gaussian integral. of course i can see that because the limits are +/- infinity, that the x integration is just going to give root pi, or 1 or something stupid easy, but I'm not terribly familiar with WHAT the actual volume is under the 3d graph of a standard gaussian, let alone a gaussian with an extra e^(tx) in it...

First perform the first integral.
If you want to walk, you need a first step.
And you will see that the second will be much easier than the first step.

That's really a general rule: don't delay the first for the reason that you do not trust the second step.
 
  • #9
You didn't write here the step where you experience a difficulty.
I can a most guess what is your problem (if any).
Therefore, I add this hint:

Exp(-2bx - (x+c)²) = Exp(-(x+b+c)² + b²) = Exp(-z²+b²) = Exp(b²) Exp(-z²)
where z = x+b+c
 

1. What is the purpose of finding the joint moment generating function given the joint PDF?

The joint moment generating function is used to calculate the moments of a continuous multivariate probability distribution. This information can be useful in understanding the shape and characteristics of the distribution, as well as in making statistical inferences.

2. How is the joint moment generating function related to the joint PDF?

The joint moment generating function is the Fourier transform of the joint PDF. It is a mathematical tool that allows us to move between the time or spatial domain (PDF) and the frequency domain (moment generating function).

3. What are the steps for finding the joint moment generating function given the joint PDF?

The steps for finding the joint moment generating function are as follows:

  1. Write out the joint PDF in terms of the variables x and y.
  2. Use the definition of the moment generating function to find the individual moment generating functions for each variable.
  3. Multiply the individual moment generating functions together to get the joint moment generating function.

4. Can the joint moment generating function be used to find the mean and variance of a distribution?

Yes, the mean and variance can be calculated from the joint moment generating function by taking the first and second derivatives, respectively, at t=0.

5. Are there any limitations to using the joint moment generating function?

One limitation is that the joint moment generating function only works for continuous distributions. It also may not exist for all distributions, in which case alternative methods would need to be used to find the moments.

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