
#1




im baffled... help with series?
I've been working on something and I dont understand where I'm going wrong.... please correct me on the following.
Let F be the cumulative distribution function of an exponential distribution with theta = 3. define w = [F(2)  F(1)] + 2[F(3)  F(2)] + 3[F(4)  F(3)] + ... w must be positive because each bracket is positive (the difference of 2 distribution functions with a higher x value minus lower x value would be a positive value) rearranging the above terms we have: w = F(1)  F(2)  F(3) + ..... Now w is a negative value?!?!? Each F is a positive value and we're adding up negative values... similarly we know S(x) = 1  F(x) substituting F(X) with S(X) in the original equation, we get w = [{1  S(2)}  {1  S(1)}] + 2[{1  S(3)}  {1  S(2)}] + 3[{1  S(4)}  {1  S(3)}] + ... w = [S(1)  S(2)] + 2*[S(2)  S(3)] + 3*[S(3)  S(4)] + .... w = S(1) + S(2) + S(3) +... WHICH IS AGAIN A POSITIVE VALUE? where am I messing up? i remember something like this in a calc class I took where if u rearrange terms in an infinite series differently, you'll get different results... how do I get the correct answer then? How do you know how to CORRECTLY rearrange terms to get the correct answer?
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Last edited by royevans; 06022018 at 06:48 PM.. 
#3




If the absolute values of all the terms does not converge the series is conditionally convergent. Conditionally convergent series can be rearranged to equal any value.
Your series does not converge absolutely as the F's are increasing to one. https://en.wikipedia.org/wiki/Riemann_series_theorem 
#4




Quote:
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#5




It's not intuitive at all, but the series written out in S's is absolutely convergent so the terms can be rearranged, but the series written out in F's is not so the terms cannot be rearranged.

#6




Quote:
The EV of the whole mixture is the expected value of the primary and secondary distribution.... the secondary distribution's (exponential) makes sense when written out in terms of the first equation I had which seems to be infinite? How would you go about finding the expected value of the billable hours? The solution just starts out with the series involving S(x) which isn't intuitive to me.
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#7




Your original series in F's is convergent (conditionally). The first term F(2)  F(1) = exp(1/3)  exp(2/3).
Factor it out then sum the remaining terms which look the the series for an increasing perpetuity due from compound interest. Cancel to simplify. you are left with: exp(1/3)/[1exp(1/3)] which is the same as the sum of the S(x)'s. You run into problems if you reorder the sequence. 
#8




So you have the number of hours in interval is
The number of hours billed for this interval is dropping the decimal portion which is so we know the expectation We also have the number of intervals as a zerotruncated geometric with . Call that . That has expectation We want the expectation of Then the answer assuming independence is No series manipulation necessary That's how I see it anyway. 
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