Assigning exponential weights depending upon sample size

AI Thread Summary
The discussion focuses on finding a function to assign exponential weights based on sample size, specifically with a sample size of 10. The user introduces a coefficient sequence and seeks to ensure that the sum of the exponential weights equals the sample size. A suggestion is made to calculate initial weights, sum them, and then adjust the weights accordingly to maintain the desired total. The conversation highlights a need for clarity regarding the definition of "exponential weights" to provide more tailored assistance. Overall, the user is looking for a method to compare exponentially weighted vectors with uniformly weighted ones.
64jnk
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I'm trying to find a function which will assign exponential weights depending upon sample size.

nu=an equally space coefficient sequence (.05,..,.5; by=.05).
m=sample size (10 in this case)

Adding each observation in nu, implies a weight of 1, which makes the sum of weights m.

I need to the exponential weights to add to m, given I'd like to compare the sum of this exponentially weighted vector to the sum of a uniformly weighted vector.

Would anyone be able to help with this please?

Many thanks,
 
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64jnk said:
I need to the exponential weights to add to m

Pick m initial exponential weights a (whatever you mean by that), add them up. Let the sum be S. Then let the final weights be w = a (m / S).

If that doesn't suit you, try explaining what you mean by "exponential weights".
 
I'm slightly embarrassed by how obvious this answer was. Thanks Stephen.
 
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