Hi The normal approach to filling a gap is to put in a point that is the average of the two adjacent points. The assumption is that this is a “safe” value that will not blow up the result. That’s probably ok if it is done rarely. The risk is that you are running a filter process (averaging is a low pass filter).
If you pull out a *lot* of outliers and replace them, you are doing a lot of filtering. Since you are measuring noise, filtering is very likely to improve the result. The question becomes - how representative is the result after a lot of this or that has been done? Obviously the answer to all this depends on what you are trying to do. If you are running a control loop and the output improves, that’s fine. If you are trying to provide an accurate measure of noise …. maybe not so much :) Bob > On Jan 19, 2021, at 2:15 AM, Gilles Clement <[email protected]> wrote: > > Hi, > Yes outliers removal creates gap in Stable32. > The « fill » function can fills gaps with interpolated values. > It does not change much the graphs, except in the low Tau area (see > attached). > Do you know a discussion of impact of outliers removal ? > Gilles. > > > >> Le 18 janv. 2021 à 22:06, Bob kb8tq <[email protected]> a écrit : >> >> Hi >> >> As you throw away samples that are far off the mean, you reduce the sample >> rate ( or at least create gaps in the record). Dealing with that could be >> difficult. >> >> Bob >> >>> On Jan 18, 2021, at 1:33 PM, Gilles Clement <[email protected]> wrote: >>> >>>> Hi >>>> >>>> Very cool !!! >>>> >>>> The red trace is obviously the one to focus on. Some sort of digital loop >>>> that >>>> only operates under the “known good” conditions would seem to make sense. >>>> >>>> Thanks for sharing >>>> >>>> Bob >>> >>> Hi, >>> I tried something with the idea to consider night records fluctuations as « >>> outliers » as compared to day records. >>> Indeed the 3 days record mean value is flat and the histogram quite >>> gaussian. >>> So I processed the 3 days record (green trace) with Stable32’s « Check >>> Function », >>> while removing outliers with decreasing values of the Sigma Factor. The >>> graph below shows the outcome. >>> The graph with Sigma=0.8 (blue trace) connects rather well with the 1Day >>> record (red trace). >>> Would this be a workable approach ? >>> Best, >>> Gilles. >>> >>> >>> >>> >>> >>> _______________________________________________ >>> time-nuts mailing list -- [email protected] >>> To unsubscribe, go to >>> http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com >>> and follow the instructions there. >> >> >> _______________________________________________ >> time-nuts mailing list -- [email protected] >> To unsubscribe, go to >> http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com >> and follow the instructions there. > > _______________________________________________ > time-nuts mailing list -- [email protected] > To unsubscribe, go to > http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com > and follow the instructions there. _______________________________________________ time-nuts mailing list -- [email protected] To unsubscribe, go to http://lists.febo.com/mailman/listinfo/time-nuts_lists.febo.com and follow the instructions there.
