A question about including the error bar with the spline.
Suppose a data point of (3,4) with error of +/- 1
(so a valid point is anywhere from (3,3) to (3,5) )
Then the spline is estimated and at that point the curve goes through (3,4.5)
So then (3,4.5) +/- 1 is between (3,3.5) and (3,5.5)
This doesn't seem right in that the 5.5 is beyond the 5
or is this just the way it works?
What is your data? Not the numbers, but the meaning of the numbers.
Where do the error bars come from?
Do you really have the same +/- 1 errors on both the x- and y-axis??
That is a little unusual.
Wouldn't that give you a unit circle around (3, 4) rather than a square?
A spline should actually go through what ever points you specify -- (3, 4) not (3, 4.5).
Your error bars (or circle) should apply to the original data, not the fitted curve.
0
Want to increase your earning potential in 2018? Pad your resume with app building experience. Learn how with this hands-on course.
Ok, so I think there is smoothing and there is interpolation. With interpolation (as in a cubic spline) the curve will go through the data points, with smoothing, the curve may miss the data point. Correct?
Smoothing implies some sort of fitting or averaging of the data.
And yes, the resultant curve may not hit any of the data points.
Curve fitting implies something else. Perhaps assuming some kind of relationship among the data points.
And a fitted curve need not pass though any of the data either.
With interpolation (linear or cubic), the curve hits all the data points and you make assumptions between points.
This is pretty standard practice.
You might plot three curves: nominal, max, and min.
This is not standard.
What is your data? And what are you trying to prove?