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Re: poly_fit for less number of points [message #84198]

Mon, 06 May 2013 13:26

Craig Markwardt
Messages: 1869
Registered: November 1996

Senior Member

On Sunday, May 5, 2013 6:03:25 PM UTC-4, David Fanning wrote:
> Craig Markwardt writes:
>
>> This fit,
>> res = poly_fit(x-mean(x), y, 2)
>> gives a smooth fit.
>
>
>
> What is the principle here that made you think of this solution and
> caused it to work?

Well, not much. He asked for a smooth function and I gave it to him. Jeremy is right, there is a round-off problem that makes the original POLY_FIT(X,Y,2) not work. Subtracting the mean of X (and/or Y) is a classic solution to the problem of round-off.

As HeinzS intimates, there's really a lot more to the question, like, how smooth should the function be? what degree of polynomial is permissible? how close of an approximation should the function be? what is the tolerance for outliers? why are there no error bars on the data? what is the definition of a "good fit?"

Without any of that information, I felt it worth to just provide *an* answer, even if it wasn't *the* answer to the original implicit question.

Craig

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[Message index]

		Re: poly_fit for less number of points By: Craig Markwardt on Mon, 06 May 2013 13:26
		Re: poly_fit for less number of points By: Heinz Stege on Mon, 06 May 2013 11:02
		Re: poly_fit for less number of points By: Jeremy Bailin on Mon, 06 May 2013 06:48
		Re: poly_fit for less number of points By: David Fanning on Sun, 05 May 2013 15:03
		Re: poly_fit for less number of points By: Craig Markwardt on Sun, 05 May 2013 12:59
		Re: poly_fit for less number of points By: sid on Sat, 04 May 2013 07:02
		Re: poly_fit for less number of points By: Heinz Stege on Sat, 04 May 2013 05:00
		Re: poly_fit for less number of points By: Craig Markwardt on Sun, 05 May 2013 12:55
		Re: poly_fit for less number of points By: Yngvar Larsen on Tue, 07 May 2013 01:20

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