- #1
oyth94
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Suppose I have the MGF moment generating function mx(t) = (e^t -1)/t
How can I find EX?
How can I find EX?
oyth94 said:Suppose I have the MGF moment generating function mx(t) = (e^t -1)/t
How can I find EX?
chisigma said:If a r.v. X has m.g.f. $\displaystyle m_{X} (t) = E \{e^{t\ X}\}$, then... $\displaystyle E\{X^{n}\} = \lim_{t \rightarrow 0} \frac{d^{n} m_{X} (t)}{d t^{n}}\ (1)$
In Your case is...
$\displaystyle E\{X\} = \lim_{t \rightarrow 0} \frac{t\ e^{t} - e^{t} + 1}{t^{2}} = \frac{1}{2}\ (2)$ Kind regards $\chi$ $\sigma$
oyth94 said:Thank you for your help. For how I did it was I used the series expansion for e^t which is the summation of (t)^k / k!
so
\(\displaystyle [(t^k / t!) - 1 ] / t\) = [(1 + t/1 + t^2 / 2! + t^3 / 3! + ...) - 1] / t
then the 1s cancel out and I can factor out the t so it becomes
= 1 + t/2! + t^2 / 3! + ...
so when i use the moment generating function
mx^(k) (0) = EX
do i sub in t=0 and then the answer will be 1?
how do I go on from there? or is the answer e?
Confused!
How do you solve it using the series expansion?
chisigma said:The result You have obtained...
$\displaystyle \frac{e^{t}-1}{t} = 1 + \frac{t}{2!} + \frac{t^{2}}{3!} + ...\ (1)$
... is absolutely correct... what is the matter?...
Kind regards
$\chi$ $\sigma$
The moment generating function is a mathematical function that provides a way to calculate the expected value (mean) and variance of a random variable. It gives us a way to represent the distribution of a random variable using its moments.
To find the expected value from the moment generating function, we simply take the first derivative of the function at t=0. This will give us the mean of the distribution. Alternatively, we can also take the second derivative of the function at t=0 to find the variance.
The moment generating function is useful because it allows us to easily find the expected value and variance of a random variable, which are important measures in probability and statistics. It also provides a way to compare different distributions and analyze their properties.
Yes, the moment generating function can be used for all types of random variables, as long as the function exists. However, it may not always be the most convenient or efficient method for finding the expected value and variance.
One limitation of the moment generating function is that it may not exist for all random variables, especially those with heavy tails or undefined moments. Additionally, it may not always be easy or feasible to find the moment generating function, particularly for complex distributions.