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Jun 24, 2016 at 0:07 comment added shai horowitz anyone have any idea how to determine if a log(x) fit or a x^y fit is better
Jun 22, 2016 at 22:11 answer added Michael E2 timeline score: 6
Jun 20, 2016 at 13:01 history tweeted twitter.com/StackMma/status/744877895944933376
Jun 20, 2016 at 5:44 vote accept shai horowitz
Jun 20, 2016 at 3:35 answer added Jack LaVigne timeline score: 7
Jun 20, 2016 at 3:12 comment added shai horowitz I have a hard time following but that just means more learning. also it shows its not as easy as I hoped.
S Jun 19, 2016 at 23:15 history edited MarcoB CC BY-SA 3.0
Formatted code
Jun 19, 2016 at 23:10 comment added MarcoB You may also be interested in the techniques shown here: mathematica.stackexchange.com/questions/114864/…
Jun 19, 2016 at 23:02 comment added JimB You might try FindMinimum where the function you're minimizing is the distance from the curve to the data point when the curve is above the data point and some large value (say, 500) when the curve is below the observed data point (i.e., a penalty for the curve being below the data). But without any mention of how the data is generated in a probabilistic manner, this is just a manipulation of the data without the ability to make statistical inferences.
Jun 19, 2016 at 23:01 review Suggested edits
S Jun 19, 2016 at 23:15
Jun 19, 2016 at 22:04 comment added shai horowitz Your right I forgot to mention i needed to do some finagling. I created the list with the first function and then reset it equal to b. the original b = didn't work.
Jun 19, 2016 at 21:52 comment added mikado I don't think the code you've posted does what you intended (I get b being Null). Can you check it?
Jun 19, 2016 at 21:46 history asked shai horowitz CC BY-SA 3.0