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An approximation algorithm is an algorithm that finds an approximate solution to a (typically NP-hard) problem. The quality of the algorithm is measured by how close to the actual optimum it performs. For example, it is a constant factor approximation algorithm if it always outputs a solution that is within a constant factor of the optimum. Hardness of approximation is one way to separate NP-hard problems.
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Computing row-sum scaled unsigned Stirling nos. of the 1st kind
As the title suggests, I would like to compute probability vectors with elements proportional to (unsigned) Stirling numbers of the first kind by row. For easy reference, here is the Wiki page.
For …
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Computing row-sum scaled unsigned Stirling nos. of the 1st kind
I was able to find a reasonably good approximation using bounds given in a tech report of Jim Pitman.
Starting on page 13 an example is worked out which computes bounds on ratios of row-adjacent St …