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My preferred solution is for FIRST to move to an all district model with 12 matches per event and therefore no more surrogates
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The criterion for "no surrogates" is M*6/T = N, where
M is the number of qual matches
T is the number of teams
N is a whole number (the number of matches played by each team)
At CMP, T=100 and M=134, so N was not a whole number; thus there were surrogates.
If instead T=96 and M=128, N would be a whole number (namely 8) and there would be no surrogates.
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Since there is a single surrogate team in an alliance we just need to add the Twitter component scores to their "Team Standing" score to get the corrected total scores for that surrogate team.
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Here's the
2013 season Twitter data for elim and qual matches. It has Archi, Curie, Galileo, & Newton. The usual Twitter data caveats apply.
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I've been playing around with maximum likelihood estimate models as an alternative (really an extension) to OPR...
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What do you mean by "maximum likelihood estimate models"
in this context?
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One more point: I'm a fan of the binary matrix approach...
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In this context, I'm assuming "the binary matrix" refers to the
2MxN design matrix [A] of the overdetermined system.
Do you then use QR factorization directly on the binary matrix to obtain the solution, or do you form the normal equations and use Cholesky?