Linear interpolation for solving uneven sampling in the platform

on Monday, November 16th, 2015 2:50 | by Christian Rohrsen

PredictionTWOThis is the prediction of one of the controls (UAS-TNTxWTB) after being interpolated for compensating for the uneven sampling. The y-axis is Correlation coeficient (taking correlation of bins of 100 sampled points) for the next 2000 sampled points (x-axis). There seems to be no decay in the prediction, as if it was a random behavior. Aparently linear interpolation is not suited for this case. I have heard that linear interpolation is fine when sampling rate variation is low (like 5%). For this case, spline interpolation might be better. If this is really worth to do I don´t know, the best case would be for sure to have the hardware to sample according to the necessities.

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Category: R code, Spontaneous Behavior

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