Calculating MGF: Solutions for Undefined Limit Issue

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Discussion Overview

The discussion revolves around the calculation of the moment generating function (MGF) for a random variable, specifically addressing an issue related to an undefined limit encountered during the computation. Participants explore the conditions under which the MGF converges and the implications of these conditions.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents the calculation of the MGF as an integral and notes that the limit involved is undefined, raising a question about how to compute the MGF under these circumstances.
  • Another participant suggests that the condition for convergence of the MGF is \( t < 1 \), arguing that this is not a limitation since the focus is on the function \( M(t) \) and its derivatives at \( t = 0 \).
  • A participant questions the reasoning behind the condition \( t - 1 > 0 \) and contrasts it with an alternative condition that \( t \) must lie within a symmetric interval around zero, specifically \( t \in (-b, b) \).
  • The same participant reiterates the integral defining the MGF and its convergence for \( t < 1 \), and introduces a series expansion for \( M(t) \) that converges for \( -1 < t < 1 \), suggesting it allows for easier computation of moments.

Areas of Agreement / Disagreement

Participants express differing views on the conditions for \( t \) regarding the convergence of the MGF, with some supporting \( t < 1 \) while others propose a broader interval. The discussion remains unresolved as participants explore these competing perspectives.

Contextual Notes

There are unresolved assumptions regarding the conditions for convergence of the MGF and the implications of different ranges for \( t \). The discussion highlights the complexity of defining the MGF in the context of undefined limits.

Usagi
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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

$\chi$ $\sigma$
 

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