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Here is what im trying to do:

Given $n$ arbitrary data points $(x_i, y_i)$ and a distribution, say $N(0,1)$. I need to produce output $(x_i, y^*_i)$ such that $y^*_i$ are weighted versions of $y_i$, where the weights are determined by the given distribution and the weights must sum to $1$.

Are there any good algorithms out there that does this?

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    Are both the Xis and Yis from the same distribution (N(0,1) in your example)? So the wis are >0 and sum to 1. How is wi determined based on f(Xi)? What is your motivation for doing this?2012-06-15

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