Removing outliers using standard deviation
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Angelavtc
am 17 Feb. 2021
Kommentiert: Angelavtc
am 19 Feb. 2021
Hello everyone,
I have a timetable of 8764*3. The first column corresponds to the date, the second to the hour (which goes from 1 to 24 in double format) and the third is a price. My objective is that, for each hour, I remove the prices that are above (Mean of that hour + 3*SD of the prices of that hour) and any price below (Mean of that hour - 3*SD of the prices of that hour). I know I could use the code:
rmoutliers(A,'mean');
However, this filter would take into account all the hours of the sample. Could someone kindly help me to apply it for each hour?
I attach here the data so you can have a clear view of what I have.
Thank you!
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Ive J
am 18 Feb. 2021
groupfilter does the trick
cleanTable = groupfilter(yourTable, 'Hour', @(x)~isoutlier(x, 'mean'), 'Price');
3 Kommentare
Ive J
am 19 Feb. 2021
Yes, outTab (complement of cleanTable) would contain outliers per each hour:
outTab = groupfilter(yourTable, 'Hour', @(x)isoutlier(x, 'mean'), 'Price');
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