How can I calculate a centered moving average with window size 7?
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I want to calculate centered moving average of daily values using a 7-day window. That is I want to start with the 4th day being the first center and continue until the 1318 as the last center. And I want the filter to proceed successively from day 4, then 5, then 6, and so on until day 1318 as the center. I have 1321 daily values. I have NaN values in blocks and scattered throughout the data but would like to keep them. I've been given the below code but because I do not know programming, I can not make sense of how I can adapt this to get what I want done. My variable is called Imn_EVI2_d. Thank you for any help.
Daywind=3.5; % window size (days/2, i.e. half of the weekly window width)
Inc=1; %Time step increment (days)
binwid = (Daywind)/1321; %Specifies bin size
start = min(1); %Specifies timestamp when dataset starts Change
last = max(1321); %Specifies timestamp when dataset ends Change
bincenter = start+binwid:(Inc/1321):(last+1); %Specifies center of bin
binnum=length(bincenter); %Specifies how many bins for window size*
Imn_EVI2_avgmovall=; %Array that moving average will go into. Right now it is empty and 0x0.
%This is a for loop that takes the bins above and averages them and takes
%the average and saves it to EVIavgmovall
for i = 1:1:(binnum);
focusday = (1 >= (bincenter(i)-binwid) & (1321 <= (bincenter(i) + binwid)));
EVI_period = Imn_EVI2_d(focusday);
d = [nan;2;3;nan;4;5;nan;6;nan;nan];
idx = isnan(d);
d(idx) = 0;
result = conv(d, ones(1,7), 'same') ./ conv(double(idx), ones(1,7), 'same');
Here not all sums over 7 neighboring elements are divided by the window width 7, but by the number of not NaNs.
More Answers (3)
Assuming each element is the measurement for one day, can't you just do
movingAverage = conv(yourData, ones(1,7), 'same');
Correct. Your answer does what I was thinking, and (trying to) describe.
Gary Kuepper on 24 Nov 2016
Why not use movmean function?
Image Analyst on 24 Nov 2016
Because when Kemal posted this almost 4 years ago, the movmean() function had not yet been introduced. Now, or actually since R2016a, you can use movmean().
nlm on 20 Feb 2020
Hi Kemal, did you find solution to your problem ? If so can you share ?
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