Remove a part of data and replace it with data to fit trend

Hello, can some one please help me with the removal of data in the photo. I tried all the outlier removals, smooth data and conventional funtions, but it is unable to detect.

[KSSV]

You have to attach your data.

[VISHNURAJ SREERAJ NAIR]

Apologies, I have attached now.

Answer 1

[Hiro Yoshino]

Try this. It removes the dent you see in the plot. Please note this also affect the both edges of the profile.

[cleanedData,outlierIndices,thresholdLow,thresholdHigh] = filloutliers(slip1,...
    "linear","movmean",29000,"ThresholdFactor",1,"SamplePoints",T1);

It would also be a good idea to detrend first and then find the outliers by using isoutlier.

[Hiro Yoshino]

I found a better solution.

1. decompose the profile into long-term, short-term and roughness profiles.
2. detect outliers in roughness and replace them with other values (linear interpolation in this case)
3. re-compose the new roughness back to the long and short profiles together

Here's the code:

[LT, ST, R] = trenddecomp(slip1);
plot(T1,LT,T1,ST,T1,R);

[Rnew,outlierIndices,thresholdLow,thresholdHigh] = filloutliers(R,...
    "linear","quartiles","SamplePoints",T1);

slip1New = Rnew + LT + ST;
plot(T1,spring1,T1,slip1New);