How to find variance and std in matlab without using zeros in matrix?

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I have a matrix (pm2d), and i need to calculate the std and (population) variance in each column without using the zero values. I was wondering if i could use a for loop or an if statement?
For my variance i used:
var = sum(pm2d.^2)/(length(pm2d)-1) - (length(pm2d))*mean(pm2d).^2/(length(pm2d)-1)
But that took the zeros into account...
And for the standard deviation i used:
S = std(pm2d)
which definitely used the zeros.
Every code i try to write is not working. Any assistance would be appreciated! Thanks!

Respuesta aceptada

Vandana Rajan
Vandana Rajan el 22 de Feb. de 2017
Editada: Vandana Rajan el 22 de Feb. de 2017
Hi,
You can use nanvar and nanstd functions in statistics toolbox.
>> b = pm2d; % just to retain the original matrix
>> b(b==0) = NaN;
>> nz_var = nanvar(b);
>> nz_std = nanstd(b);
Of course, this solution works only if you have license to statistics toolbox.
  2 comentarios
Leesy
Leesy el 22 de Feb. de 2017
I do not, is there another way to do it?
Rik
Rik el 22 de Feb. de 2017
Editada: Rik el 12 de En. de 2018
Yes. My solution, or the one Jan Simon suggested (which should have better performance).

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Más respuestas (2)

Rik
Rik el 22 de Feb. de 2017
In my solution, I abuse the option of omitting NaNs when using mean and std
pm2d_temp=pm2d;%create a copy
pm2d_temp(pm2d_temp==0)=NaN;%overwrite zeroes with NaN
var = sum(pm2d.^2)/(length(pm2d)-1) - (length(pm2d))*mean(pm2d_temp,'omitnan').^2/(length(pm2d)-1)
S=std(pm2d_temp,'omitnan');

Jan
Jan el 22 de Feb. de 2017
Editada: Jan el 22 de Feb. de 2017
It works with replacing the zeros by NaNs and ignoring the NaNs, but you can do this directly also:
function [m, v, s] = StatsNonZeros(x, dim)
if nargin < 2 % Default: first non-singelton dimension
dimv = [find(size(x) ~= 1), 1]; %#ok<MXFND>
dim = dimv(1);
end
n = sum(x ~= 0, dim); % Number of non zero elements along dim
m = sum(x, dim) ./ n; % Zeros are neutral in the sum
v = sum(bsxfun(@minus, x, m) .^ 2, dim) ./ (n - 1);
s = sqrt(v);
end
This is what happens inside nanmean and nanstd also, after the NaNs have been replaced by zeros. Therefore it is an indirection to replace the zeros by NaNs at first.
Call it as:
[m,v,s] = StatsNonZero(pm2d)
  2 comentarios
Franck Eitel
Franck Eitel el 29 de Nov. de 2017
What's the meaning of 's' here? I think we were looking for the variance and standard deviation. Pls could you clarify it for me?
Rik
Rik el 12 de En. de 2018
[m, v, s] are the mean, variance, and standard deviation, although I presume you will have found that by now.

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