MHB Calculating MGF: Solutions for Undefined Limit Issue

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The discussion centers on calculating the moment generating function (MGF) and addressing an undefined limit issue. The MGF is defined as M(t) = E(e^{tX}) = ∫₀^∞ e^{xt} e^{-x} dx, which converges for t < 1, yielding M(t) = 1/(1-t). Participants clarify that the condition t < 1 is crucial for convergence, while the series expansion M(t) = ∑ₙ₌₀^∞ tⁿ also converges for -1 < t < 1. The conversation emphasizes the importance of these conditions for computing moments effectively.
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http://img253.imageshack.us/img253/7306/moments.jpg

This a pretty weird question... because:

E(e^{tX}) = M(t) = \int_0^{\infty} e^{xt} e^{-x} dx = \int_0^{\infty} e^{-x(1-t)}dx = \lim_{k \to \infty} \left[\frac{e^{x(t-1)}}{t-1}\right]_0^k

But the limit: \lim_{k \to \infty} \left[\frac{e^{k(t-1)}}{t-1}\right] is undefined?

How am I meant to compute the MGF then?

Thanks
 
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Usagi said:
http://img253.imageshack.us/img253/7306/moments.jpg

This a pretty weird question... because:

E(e^{tX}) = M(t) = \int_0^{\infty} e^{xt} e^{-x} dx = \int_0^{\infty} e^{-x(1-t)}dx = \lim_{k \to \infty} \left[\frac{e^{x(t-1)}}{t-1}\right]_0^k

But the limit: \lim_{k \to \infty} \left[\frac{e^{k(t-1)}}{t-1}\right] is undefined?

How am I meant to compute the MGF then?

Thanks

If $\displaystyle 1-t>0 \implies t<1$ is...

$\displaystyle E\{e^ {t\ X}\}= \int_{0}^{\infty} e^{-x\ (1-t)}\ dx = - |\frac{e^{-x\ (1-t)}}{1-t}|_{0}^{\infty} = \frac{1}{1-t}$ (1)

The condition $t<1$ is no limitation because pratically we are interested to the function $M(t)$ and its derivatives in $t=0$...

Kind regards

$\chi$ $\sigma$
 
Last edited:
Thanks chisigma,

However how did you know to set t-1>0? I thought the restriction on t was that there exists a positive b, such that t \in (-b,b)

How does that relate with setting t-1>0 though?

Thanks again
 
Usagi said:
Thanks chisigma,

However how did you know to set t-1>0? I thought the restriction on t was that there exists a positive b, such that t \in (-b,b)

How does that relate with setting t-1>0 though?

Thanks again

The integral defining the moment generating function...

$\displaystyle M(t)= E\{e^{t\ X}\}= \int_{0}^{\infty} e^{-x\ (1-t)}\ dx$ (1)

... converges for $\displaystyle t<1$ to $\displaystyle M(t)= \frac{1}{1-t}$. The series expansion...

$\displaystyle M(t)= \frac{1}{1-t}= \sum_{n=0}^{\infty} t^{n}$ (2)

... converges for $\displaystyle -1<t<1$ and (2) allows You an easily computation of the moments...

$\displaystyle E\{X^{n}\}= M^{(n)}(0)= n!$ (3)

Kind regards

$\chi$ $\sigma$
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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