Find the MGF of geometric,neg binomial dist.

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Homework Help Overview

The discussion revolves around finding the moment generating function (MGF) for the geometric and negative binomial distributions. Participants are examining the definitions and formulas associated with these distributions.

Discussion Character

  • Mixed

Approaches and Questions Raised

  • Some participants attempt to derive the MGF for the geometric distribution using series summation, while others question the correctness of the provided formulas for both distributions. There is a discussion about the differences in definitions found in various sources.

Discussion Status

Participants are actively engaging with the problem, exploring different interpretations of the distributions and their MGFs. Some have made progress in their calculations, while others are clarifying definitions and questioning assumptions about the formulas used.

Contextual Notes

There are indications of confusion regarding the correct forms of the geometric and negative binomial distributions, as well as the implications of summing from different starting points in series. Participants are also considering the relationship between the MGF of a sum of independent random variables and the distributions in question.

ArcanaNoir
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Homework Statement



Find the MGF (Moment generating function) of the
a. geometric distribution
b. negative binomial distribution

Homework Equations



geometric distribution: [tex]f(x)=p^x(1-p)^{x-1}[/tex] where x=1,2,3...

negative binomial distribution: [tex]f(x)= \frac{(x-1)!}{(x-r)!(r-1)!}p^r(1-p)^{x-r}[/tex] where x=r, r+1, r+2...

MGF= [tex]E(e^{tx})[/tex]

The Attempt at a Solution



a. [tex]\sum_{x=1}^{\infty}e^{tx}p^x(1-p)^{x-1}[/tex]
let [itex]q=1-p[/itex]
[tex]\sum_{x=1}^{\infty}e^{tx}p^xq^{x-1}[/tex]
[tex]\sum_{x=0}^{\infty}(pe^t)q^x[/tex]
[tex]=\frac{pe^t}{1-q}[/tex]
that's as close as I can get to approximating the solution,
but the book says the answer is [tex]\frac{pe^t}{1-qe^t}[/tex]

b. [tex]\sum_{x=r}^{\infty}\frac{(x-1)!}{(x-r)!(r-1)!}e^{tx}p^rq^{x-r}[/tex] where q=1-p
 
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ArcanaNoir said:

Homework Statement



Find the MGF (Moment generating function) of the
a. geometric distribution
b. negative binomial distribution

Homework Equations



geometric distribution: [tex]f(x)=p^x(1-p)^{x-1}[/tex] where x=1,2,3...

negative binomial distribution: [tex]f(x)= \frac{(x-1)!}{(x-r)!(r-1)!}p^r(1-p)^{x-r}[/tex] where x=r, r+1, r+2...

Those aren't the distributions I'm used to. Are you sure these formula's are correct??

For the geometric distribution, I got

[tex]f(x)=p^x(1-p)[/tex]

and the negative binomial is

[tex]f(x)=\binom{x+r-1}{x}(1-p)^rp^x[/tex]

Could you recheck this first?
 
oh good god. I was looking at point binomial.
so here's what I get now,
[tex]\sum_{x=1}^{\infty}e^{tx}p(1-p)^{x-1}[/tex] letting q= (1-p)
[tex]= \frac{p}{q} \sum_{x=1}^{\infty}e^{tx}q^{x}[/tex]
[tex]= \frac{p}{q} \sum_{x=1}^{\infty}(e^{t}q)^x[/tex]
 
ArcanaNoir said:
oh good god. I was looking at point binomial.
so here's what I get now,
[tex]\sum_{x=1}^{\infty}e^{tx}p(1-p)^{x-1}[/tex] letting q= (1-p)
[tex]= \frac{p}{q} \sum_{x=1}^{\infty}e^{tx}q^{x}[/tex]
[tex]= \frac{p}{q} \sum_{x=1}^{\infty}(e^{t}q)^x[/tex]

Yes, go on... You have a geometric series right now.
 
the negative binomial I have as being : [tex]\binom{x-1}{r-1} p^r(1-p)^{x-r}[/tex]
which I figured equals : [tex]\frac{(x-1)!}{(x-1-(r-1))!(r-1)!}p^r(1-p)^{x-r}[/tex]
[tex]= \frac{(x-1)!}{(x-r)!(r-1)!}p^r(1-p)^{x-r}[/tex]
 
micromass said:
Yes, go on... You have a geometric series right now.

so, [itex]\frac{1}{1-r}[/itex] ?
[tex]( \frac{p}{q} ) \frac{1}{1-e^{t}q}[/tex] ?
 
ArcanaNoir said:
so, [itex]\frac{1}{1-r}[/itex] ?
[tex]( \frac{p}{q} ) \frac{1}{1-e^{t}q}[/tex] ?

That's the sum of the geometrci series when you start summing from 0. But you start summing from 1 here.
 
but if I sum from zero, won't I have [tex]\frac{p}{q} \sum_{x=0}^{\infty}(e^{t}q)^{x+1}[/tex] oh wait. I see. hold on
 
  • #10
nevermind. I don't see. am I suppose to have x-1 at x=0 to do the sum?
 
  • #11
oop, there it is! found the answer to the geometric. thanks for the support on that.
 
  • #12
ArcanaNoir said:

Homework Statement



Find the MGF (Moment generating function) of the
a. geometric distribution
b. negative binomial distribution

Homework Equations



geometric distribution: [tex]f(x)=p^x(1-p)^{x-1}[/tex] where x=1,2,3...

negative binomial distribution: [tex]f(x)= \frac{(x-1)!}{(x-r)!(r-1)!}p^r(1-p)^{x-r}[/tex] where x=r, r+1, r+2...

MGF= [tex]E(e^{tx})[/tex]

The Attempt at a Solution



a. [tex]\sum_{x=1}^{\infty}e^{tx}p^x(1-p)^{x-1}[/tex]
let [itex]q=1-p[/itex]
[tex]\sum_{x=1}^{\infty}e^{tx}p^xq^{x-1}[/tex]
[tex]\sum_{x=0}^{\infty}(pe^t)q^x[/tex]
[tex]=\frac{pe^t}{1-q}[/tex]
that's as close as I can get to approximating the solution,
but the book says the answer is [tex]\frac{pe^t}{1-qe^t}[/tex]

b. [tex]\sum_{x=r}^{\infty}\frac{(x-1)!}{(x-r)!(r-1)!}e^{tx}p^rq^{x-r}[/tex] where q=1-p

The negative binomial with parameters p and r is the distribution of a sum of r independent geometric random variables with parameter p. What do you know about the MGF of a sum of independent random variables?

RGV
 

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