Timeline for How to evaluate an interpolation method, in terms of converging to the underlying function, as data points go to infinity?
Current License: CC BY-SA 4.0
7 events
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| Oct 30, 2019 at 20:53 | comment | added | Gerry Myerson | Yes, that might be good enough for your purposes, just asking for the points to be dense in the domain. It's only if you want the average of the approximation to converge to the integral of the function that you need the stronger condition of uniform distribution. | |
| Oct 30, 2019 at 14:15 | comment | added | Rajesh D | @GerryMyerson : Thats is a much stronger condition? I am not interested in uniform distribution, but, something like, given any open subset, the sequence contains atleast one point from it, if we make $N$ sufficiently large. I think this would work, but I don't know if it is known by any name. | |
| Oct 30, 2019 at 11:45 | comment | added | Gerry Myerson | There's a concept of a uniformly distributed sequence of points. It means that for every interval the difference between the proportion of the domain contained in the interval and the proportion of points contained in the interval approaches zero. | |
| Oct 30, 2019 at 11:43 | comment | added | Rajesh D | @GerryMyerson : you mean define a probability distribution for the points? | |
| Oct 30, 2019 at 11:39 | comment | added | Gerry Myerson | You could insist that the sequence of points be uniformly distributed. | |
| Oct 30, 2019 at 2:33 | history | edited | Rajesh D | CC BY-SA 4.0 |
added 5 characters in body
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| Oct 30, 2019 at 2:11 | history | asked | Rajesh D | CC BY-SA 4.0 |