How do I compute 3 minute moving average in timeseries?
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Sirish Selvam
on 14 Mar 2019
Answered: sudharshini
on 10 Sep 2024 at 3:41
I have a time series object with two columns : Date,time (dd-mm-yyyy HH:MM:SS format) and Value. The data is sampled every 2 seconds. The total data is available is for around 10 days. How do I compute a timeseries with 3-minute moving average values?
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Accepted Answer
Image Analyst
on 14 Mar 2019
3 minutes at every 2 seconds would be about 91 elements, so use movmean():
movingAverageSignal = movmean(signal, 91);
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Chris Turnes
on 15 Mar 2019
If the times are stored as datetimes, you don't even need to figure out that it's about 91 elements; you can do
y = movmean(x, minutes(3), 'SamplePoints', timestamps)
More Answers (3)
Peter Perkins
on 15 Mar 2019
If you mean, "means for each 3-minute time window", consider using a timetable and the retime function. If you mean, "means at each 2-sec step over the previous 3 minutes", you can also do that on a timetable, using smoothdata.
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nlm
on 7 May 2020
How to calculate a 10 day average when the timeseries has duplicate dates. I do not want to average the dupliate dates priorly. I want to include them in the 10 day average. When I use movmean, I get this error, any suggestions ?
Error using builtin
'SamplePoints' value contains duplicates.
Error in datetime/movmean (line 105)
y = builtin('_movmeandt', args{:});
Andrei Bobrov
on 14 Mar 2019
Let ts - your timeseries object.
k = 3*60/2; % the number of elements corresponding to three minutes in your case
ts.Data(:,2) = movmean(ts.Data,[0, k - 1]);
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