Assigning exponential weights depending upon sample size

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SUMMARY

The discussion focuses on assigning exponential weights based on sample size, specifically using a coefficient sequence defined as nu = (.05, .10, .15, .20, .25, .30, .35, .40, .45, .50) with a sample size (m) of 10. The goal is to compare the sum of exponentially weighted vectors to uniformly weighted vectors. A proposed solution involves calculating initial weights a[i], summing them to obtain S, and then adjusting the weights using the formula w[i] = a[i] (m / S). The need for clarity on the definition of "exponential weights" was also highlighted.

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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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