Sums of exponentially distributed rvs

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roadworx
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Hi,

Can anyone derive the sum of exponentially distributed random variables?

I have the derivation, but I'm confused about a number of steps in the derivation.

Here they are:

Random variable x has the PDF,

[tex]f(s) = \left\{<br /> \begin{array}{c l}<br /> e^{-s} & if s \ge 0 \\<br /> 0 & otherwise <br /> \end{array}<br /> \right. [/tex]

Let [tex]X_1, X_2, ... , X_n[/tex] be independently exponentially distributed random variables.

The PDF of the sum, [tex]X_1 + X_2 + ... +X_n[/tex] is

[tex]q(s) = e^{-(s_1+s_2+...+s_n)}[/tex] where s [tex]s \ge 0[/tex]

=> [tex]\int_{a \le s_1+s_2+...+s_n \le b} q(s) ds[/tex]

= [tex]\int_{a \le s_1+s_2+...+s_n \le b} e^{-(s_1 + ... + s_n)} ds[/tex]

Can anyone explain this stage? Going from the above integral to the following integral?

= [tex]\int^b_a e^{-u} vol_{n-1} T_u du[/tex]

where [tex]T_u = [s_1+ ... + s_n = u][/tex]


What would [tex]vol_{n-1}[/tex] be here?
 
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Do you need to do the problem this way? I can suggest two procedures that would be easier than this approach:
1) Since the [tex]X[/tex]s are i.i.d exponential, you can calculate the moment generating function of the sum quite easily, and identify the distribution from that
2) Rather than using all [tex]n[/tex] of the variables in a single integration, start with

[tex] S_2 = X_1 + X_2[/tex]

and find its distribution, then continue to the case you have by induction.