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Timeline for variability among signals

Current License: CC BY-SA 3.0

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Oct 16, 2015 at 20:57 answer added Emanuel Landeholm timeline score: 0
Oct 15, 2015 at 19:15 vote accept Niels Janssen
Oct 15, 2015 at 15:25 answer added Peter K. timeline score: 0
Oct 15, 2015 at 13:11 comment added Niels Janssen Good point. The signals are fMRI BOLD, which is usually modeled using a double gamma function. I think you are right that this the way to go. Modeling the signals would then allow me to examine the variability of many different parameters that correlation alone ignores. Thanks for the advice.
Oct 15, 2015 at 12:46 comment added Peter K. What variations do you expect to see between the different signals? Can you model $y_k$ so that you can parameterize these variations? That might give us a better clue as to how to help. Sometimes signals that are closer to deterministic than random don't work as well as you'd like with correlations.
Oct 15, 2015 at 12:44 history edited Peter K. CC BY-SA 3.0
Removed double-sigma it's either summation OR + + + not both.... I think.
Oct 15, 2015 at 12:01 history edited Niels Janssen CC BY-SA 3.0
added 12 characters in body
Oct 15, 2015 at 10:59 history edited jojeck CC BY-SA 3.0
added 6 characters in body
Oct 15, 2015 at 10:16 history edited Niels Janssen CC BY-SA 3.0
deleted 8 characters in body
Oct 15, 2015 at 10:09 history edited Niels Janssen CC BY-SA 3.0
added math
Oct 15, 2015 at 9:50 history edited Niels Janssen CC BY-SA 3.0
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Oct 15, 2015 at 9:50 comment added Marcus Müller I'm not quite sure I can 100% visualize the math you want to do. Why not add mathematical formulas to the question, like $\bar y = \sum\ldots$, so that we can discuss this on a definite basis?
S Oct 15, 2015 at 9:48 history suggested Gilles CC BY-SA 3.0
improved formatting
Oct 15, 2015 at 9:23 review Suggested edits
S Oct 15, 2015 at 9:48
Oct 15, 2015 at 7:48 review First posts
Oct 15, 2015 at 10:59
Oct 15, 2015 at 7:44 history asked Niels Janssen CC BY-SA 3.0