extrapolating data with numpy/python - Stack Overflow
https://stackoverflow.com/questions/1940604915.10.2013 · Since your data is approximately linear you can do a linear regression, and then use the results from that regression to calculate the next point, using y = w[0]*x + w[1] (keeping the notation from the linked example for y = mx + b).. If your data is not approximately linear and you don't have some other theoretical form for a regression, then general extrapolations (using say …
How can i extrapolate data? - MathWorks
www.mathworks.com › matlabcentral › answersMar 27, 2020 · However, with only 4 data points, there is no simple way to intelligently extrapolate your data. That is, we might do this: mdl = fit (fs (6:9)',P (6:9)','poly3') which fits a cubic polynomial through the 4 data points you have. I'm not at all confidant that an interpolating polynomial is a good idea though, and extrapolating all the way down ...
Extrapolation - Wikipedia
https://en.wikipedia.org/wiki/ExtrapolationIn complex analysis, a problem of extrapolation may be converted into an interpolation problem by the change of variable . This transform exchanges the part of the complex plane inside the unit circle with the part of the complex plane outside of the unit circle. In particular, the compactification point at infinity is mapped to the origin and vice versa. Care must be taken with this transform however, since the original function may have had "features", for example polesan…
How To Extrapolate In Excel - BSUPERIOR
bsuite365.com › blog › excelAug 12, 2020 · To extrapolate data by formula, we need to use two points of the linear chart that we plotted before. A (a, b) B (c, d) The linear extrapolation formula is: Y (x)=b+ (x-a)* (d-b)/ (c-a) You can enter the formula according to two points of your data values and extrapolate the target value. Picture 1- The linear extrapolation formula in Excel.