Basics of moment generating functions

In summary, the conversation discusses finding the moment generating function of f_X(x)=e^{-x}, x>0 and the process of applying the expectation in this case. The solution is shown using the definition of moment-generating function and the expectation can be easily found after deriving the function. Additional resources are suggested for a better understanding.
  • #1
Mentallic
Homework Helper
3,802
95
I missed my class that introduced us to moment generating functions, and my notes are missing some pretty essential parts to helping me understand them, so here it is:


Homework Statement



Find the moment generating function of [itex]f_X(x)=e^{-x}, x>0[/itex]



Homework Equations



[tex]E(X^R)=\int_{-\infty}^{\infty}X^Rf_X(x)dx[/tex]

R must be a natural number I believe.

[tex]m_X(u) = E(e^{uX})[/tex]



The Attempt at a Solution



I'm unsure if the expectation is applied in the same way, in other words, would this be correct?

[tex]m_X(u) = E(e^{ux})[/tex]

[tex]= \int_{-\infty}^{\infty}e^{uX}f_X(x)dx[/tex]

[tex]= \int_{0}^{\infty}e^{ux}e^{-x}dx[/tex]

[tex]= \int_{0}^{\infty}e^{x(u-1)}dx[/tex]

And I'm not quite sure what the u in this case is either.
 
Physics news on Phys.org
  • #3
Oh awesome, thanks vela.

I can also see that the expectation can be found quite easily after deriving the moment generating function, which is good because I'll be needing it :smile:
 

1. What is a moment generating function (MGF)?

A moment generating function is a mathematical function that is used to describe the probability distribution of a random variable. It is defined as the expected value of e^(tx), where t is a variable and x is the random variable.

2. Why is the MGF important in statistics?

The MGF is important in statistics because it allows us to find the moments of a distribution, such as its mean, variance, skewness, and kurtosis. These moments can then be used to describe and compare different distributions.

3. What is the relationship between the MGF and the probability distribution function (PDF)?

The MGF and PDF are closely related, as the MGF uniquely determines the PDF of a distribution. In other words, if two distributions have the same MGF, then they have the same PDF.

4. How is the MGF used in hypothesis testing?

The MGF is used in hypothesis testing to determine the parameters of a distribution. By finding the MGF of a random variable, we can compare it to the MGF of a known distribution and determine if the two are significantly different, thus supporting or rejecting a hypothesis.

5. Are there any limitations to using MGFs?

Yes, there are some limitations to using MGFs. They may not exist for all distributions, and even when they do exist, they may not be easy to calculate. Additionally, the MGF only provides information about the moments of a distribution and may not fully describe its shape or characteristics.

Similar threads

  • Calculus and Beyond Homework Help
Replies
7
Views
927
  • Calculus and Beyond Homework Help
Replies
31
Views
2K
  • Calculus and Beyond Homework Help
Replies
3
Views
627
  • Calculus and Beyond Homework Help
Replies
5
Views
611
  • Calculus and Beyond Homework Help
Replies
3
Views
1K
  • Calculus and Beyond Homework Help
Replies
8
Views
985
  • Calculus and Beyond Homework Help
Replies
9
Views
949
  • Calculus and Beyond Homework Help
Replies
15
Views
1K
  • Calculus and Beyond Homework Help
Replies
2
Views
838
  • Calculus and Beyond Homework Help
Replies
1
Views
692
Back
Top