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open-connectome-classes / StatConn-Spring-2015-Info

introductory material
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Mean Connectome Decision Rule #139

Open indigorose1 opened 9 years ago

indigorose1 commented 9 years ago

So from what I understand, the decision rule has to do with p-hat = (1/m) \sum_1^m A^{(i)}, but I'm having trouble interpreting what this means. What does the A to the (i) mean?

ghost commented 9 years ago

I believe it was written as the sum of i to m, where m is the number of trials (or number of brains you scan). So the whole equation is taking the average, where A^{i} represents the adjacency matrix built from each brain. A is the adjacency matrix, is is the ith brain.

yaxigeigei commented 9 years ago

Based on a online tutorial (http://www.youtube.com/playlist?list=PLD0F06AA0D2E8FFBA, episode 11.2 & 11.3) and my personal understanding, the decision rule is equivalent to the estimator for estimating the mean theta (theta_hat), i.e. it is a function f that theta_hat = f(Data). Anyway, the video explain it much better than I could.

indigorose1 commented 9 years ago

Thanks for that playlist! It helps a lot.