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as a linear approximation is used to approximate a point between two points. how can we apply linear or other approximation when multiple points are given and we have to approximate a single point using all of them. For example as in linked picture green points are the point i know already and i want estimate points at 10 ms , 20 ms and 30 ms ... e.g, for 10 ms point i want to use all point between 0-20 ms to estimate 10 ms point and so on enter image description here

emma
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Salman Shaukat
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  • You got to be more specific in this case. Since you say approximation and not interpolation, I would take it as an approximation. To approximate a point in a "cloud" of points you can use the least square method. This is similar to what Excel uses when fitting a function to a set of points. – Snifkes May 11 '18 at 17:14
  • there multiple averaging / interpolation / extrapolation techniques. You might want to add more context. – user251257 May 11 '18 at 17:14
  • @Snifkes i hope it is clear now after adit – Salman Shaukat May 11 '18 at 17:28
  • Once again, do you want to use an interpolation or approximation. The difference comes down to: do you know what the movement should look like?(linear, quadratic polynomial, etc.) in this case, use least squares approximation. On the other hand, is the data absolutely accurate and you want to fit a function to it without necessarily knowing how the function suppose to look like? use polynomial, spline or any other interpolation technique. The main difference comes down to: do I trust my data absolutely (= interpolation), do I have a model I try to follow and data my be faulty (= approximation) – Snifkes May 11 '18 at 17:34
  • @Snifkes Thanks for explaining, and yes my data is accurate. so i'll try to implement spline or polynomial interpolation – Salman Shaukat May 11 '18 at 17:43

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