Re: discrete random variable
- From: Niels Diepeveen <n936673@xxxxxxxxxxxx>
- Date: Mon, 04 Feb 2008 12:46:39 +0100
zqchen wrote:
On Feb 1, 9:23 am, Niels Diepeveen <n936...@xxxxxxxxxxxx> wrote:
Remember that for a sum of nonnegative numbers (such as probabilities)could you give an example that sum converges or doesn't if calculated
convergence implies absolute convergence, so you can calculate the sum in
any convenient order.
in different order? thanks
If you search the sci.math archive for "conditionally convergent", you'll
find many interesting discussions of this. However, I didn't see many
simple concrete examples so here are some variations on the standard
example,
log 2 = 1 - 1/2 + 1/3 - 1/4 + 1/5 ...
If you reorder this as in exponentially increasing groups of positive and
negative terms, like this
1
- 1/2
+ 1/3 + 1/5
- 1/4 - 1/6
+ 1/7 + 1/9 + 1/11 + 1/13
- 1/8 - 1/10 - 1/12 - 1/14
+ 1/15 + 1/17 + 1/19 + 1/21 + 1/23 + 1/25 + 1/27 + 1/29
- 1/16 - 1/18 - 1/20 - 1/22 - 1/24 - 1/26 - 1/28 - 1/30
....
you can easily see that the absolute value of each group must be greater
than 1/4, because each group has 2^k terms greater than 2^(-k-2).
This is enough to show that the series doesn't converge.
To be more precise, in this order the partial sums still have a liminf of
log 2, but they also have a limsup of 3/2 log 2. If you let the size of the
groups grow even faster, you can get even wilder divergence.
At least as importantly, you can reorder the terms to make the sum converge
to a different limit, for example
(1 - 1/2 - 1/4) + (1/3 - 1/6 - 1/8) + (1/5 - 1/10 - 1/12) + ... =
(1/2 - 1/4) + (1/6 - 1/8) + (1/10 - 1/12) + .... =
(1 - 1/2 + 1/3 - 1/4 + 1/5 - 1/6 + ....) / 2 = (log 2) / 2
--
Niels Diepeveen
.
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