Moments from characteristic function geometric distribution

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Homework Help Overview

The discussion revolves around the characteristic function of a geometric distribution, specifically focusing on the probability density function given by ##p_{n}=(1-p)^{n}p## for ##n=0,1,2...## Participants are tasked with finding the characteristic function ##p(k)= ## and using it to derive the mean and variance of the distribution.

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the derivation of the characteristic function and share their attempts at manipulating the series involved. There is a focus on comparing different methods of summing the series and equating coefficients to find moments. Some participants express confusion about the validity of their approaches and seek clarification on specific steps.

Discussion Status

The discussion is ongoing, with participants exploring different methods to derive the characteristic function. Some have provided insights into the correct approach, while others are questioning the validity of their own reasoning and the assumptions made in their calculations.

Contextual Notes

Participants are working under the constraints of homework guidelines, which may limit the amount of direct assistance they can receive. There is an emphasis on understanding the steps involved rather than simply arriving at the final answer.

binbagsss
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Homework Statement



Hi,

I have the probability density: ##p_{n}=(1-p)^{n}p , n=0,1,2... ##

and I am asked to find the characteristic function: ##p(k)= <e^{ikn}> ## and then use this to determine the mean and variance of the distribution.

Homework Equations


[/B]
I have the general expression for the characteristic function : ##\sum\limits^{\infty}_{n=0} \frac{(-ik)^m}{m!} <x^{m}> ## * , from which can equate coefficients of ##k## to find the moments.

The Attempt at a Solution



So I have ## <e^{-ikn}>=\sum\limits^{\infty}_{n-0} (1-p)^{n}p e^{-ikn} ##

I understand the solution given in my notes which is that this is equal to, after some rearranging etc, expanding out using taylor :

## 1 + \frac{(1-p)}{ p} (-k + 1/2 (-ik)^{2} + O(k^3) ) + \frac{(1-p)^{2}} { p^2 } ( (-ik)^{2} + O(k^3))##
and then equating coefficients according to *

However my method was to do the following , and I'm unsure why it is wrong:

## <e^{-ikn}>=\sum\limits^{\infty}_{n=0} (1-p)^{n} p e^{-ikn} = \sum\limits^{\infty}_{n=0} (1-p)^{n}p \frac{(-ik)^n}{n!} ##

And so comparing to * ## \implies ##

## \sum\limits^{\infty}_{n=0} (1-p)^{n}p = \sum\limits^{\infty}_{n=0} <x^{n}> ##

Anyone tell me what I've done wrong? thank you, greatly appreciated.
 
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binbagsss said:

Homework Statement



Hi,

I have the probability density: ##p_{n}=(1-p)^{n}p , n=0,1,2... ##

and I am asked to find the characteristic function: ##p(k)= <e^{ikn}> ## and then use this to determine the mean and variance of the distribution.

Homework Equations


[/B]
I have the general expression for the characteristic function : ##\sum\limits^{\infty}_{n=0} \frac{(-ik)^m}{m!} <x^{m}> ## * , from which can equate coefficients of ##k## to find the moments.

The Attempt at a Solution



So I have ## <e^{-ikn}>=\sum\limits^{\infty}_{n-0} (1-p)^{n}p e^{-ikn} ##

I understand the solution given in my notes which is that this is equal to, after some rearranging etc, expanding out using taylor :

## 1 + \frac{(1-p)}{ p} (-k + 1/2 (-ik)^{2} + O(k^3) ) + \frac{(1-p)^{2}} { p^2 } ( (-ik)^{2} + O(k^3))##
and then equating coefficients according to *

However my method was to do the following , and I'm unsure why it is wrong:

## <e^{-ikn}>=\sum\limits^{\infty}_{n=0} (1-p)^{n} p e^{-ikn} = \sum\limits^{\infty}_{n=0} (1-p)^{n}p \frac{(-ik)^n}{n!} ##

And so comparing to * ## \implies ##

## \sum\limits^{\infty}_{n=0} (1-p)^{n}p = \sum\limits^{\infty}_{n=0} <x^{n}> ##

Anyone tell me what I've done wrong? thank you, greatly appreciated.

Simplify:
$$p (1-p)^n e^{-ikn} = p x^n, \; \text{where} \; x = (1-p)e^{-ik}$$
Now just sum the geometric series ##\sum x^n##.
 
Ray Vickson said:
Simplify:
$$p (1-p)^n e^{-ikn} = p x^n, \; \text{where} \; x = (1-p)e^{-ik}$$
Now just sum the geometric series ##\sum x^n##.

Yeah that's fine, and in the end you get the 'solution given' which I said I understand. That's what's been done before expanding out.

My problem was wondering what is wrong with the method I post after that...
 
Last edited:
binbagsss said:
Yeah that's fine, and in the end you get the 'solution given' which I said I understand. That's what's been done before expanding out.

My problem was wondering what is wrong with the method I post after that...

You seem to be saying that ##p(1-p)^n e^{-ikn}## is the same as ##p(1-p)^n (-ik)^n/n!##, but this is obviously false.
 
Last edited:
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