mean value of each row
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I have A 500 by 16 matrix and I want to find a mean value of each row and return the result as a 500 by 1.
Does anyone have an idea?
Thank you
2 commentaires
Walter Fanka
le 15 Juil 2018
Modifié(e) : Walter Roberson
le 17 Juil 2018
y = yourmatrix;
meanrow_y = mean(y')'
Walter Roberson
le 17 Juil 2018
That should work for 2D arrays like were asked about. However for 3 or more dimensions it would not work and you would need to use a couple of permute() instead. It is a lot easier to just pass in the dimension number like I showed in my Answer.
Réponse acceptée
Walter Roberson
le 5 Fév 2012
mean(YourMatrix,2)
4 commentaires
Jan
le 15 Mar 2017
The documentation of mean explains this exhaustively already:
doc mean
The first input is the data, the 2nd the dimension to operate on. Therefore mean(x,2) is the mean over the 2nd dimension, which means the rows.
Amy Gleckl
le 20 Déc 2019
I had a similar issue and this worked perfectly for me, thank you very much!
Plus de réponses (2)
sura Naji
le 25 Oct 2019
l have amatrix contact from 1 colum and 1000 rows l want to find the mean and the standard deviation also l want to find the worst value of this because l use the particle swarm optimization
1 commentaire
Walter Roberson
le 22 Déc 2019
M = mean(amatrix);
S = std(amatrix);
[~, order] = max(abs(amatrix - M));
furthest_from_mean = amatrix(order(1));
Note that the value that is furthest from the mean will also be the value that is the greatest zscore (furthest deviation)
RAMPUNIT KUMAR
le 2 Sep 2021
RAMPUNIT KUMAR less than a minute ago ⋮ I too have a doubt, like for matrix (a b c d e f g h I j k l m n o p q r) I need to find the mean of a,b then c,d then e,f then g,h and so on upto last element. How could we do that if size is big enough.
1 commentaire
Walter Roberson
le 2 Sep 2021
syms a b c d e f g h I j k l m n o p q r
matrix = [a b c d e f g h I j k l m n o p q r]
means = (matrix(1:2:end) + matrix(2:2:end))/2
except that you would use the appropriate numeric values in matrix instead of syms . The syms used here is just for demonstration purposes.
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