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

조회 수: 14 (최근 30일)
Leesy
Leesy 2017년 2월 22일
댓글: Rik 2018년 1월 12일
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!

채택된 답변

Vandana Rajan
Vandana Rajan 2017년 2월 22일
편집: Vandana Rajan 2017년 2월 22일
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.
  댓글 수: 2
Leesy
Leesy 2017년 2월 22일
I do not, is there another way to do it?
Rik
Rik 2017년 2월 22일
편집: Rik 2018년 1월 12일
Yes. My solution, or the one Jan Simon suggested (which should have better performance).

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추가 답변 (2개)

Rik
Rik 2017년 2월 22일
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 2017년 2월 22일
편집: Jan 2017년 2월 22일
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This is what happens inside nanmean and nanstd also, after the NaNs have been replaced by zeros.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)
  댓글 수: 2
Franck Eitel
Franck Eitel 2017년 11월 29일
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 2018년 1월 12일
[m, v, s] are the mean, variance, and standard deviation, although I presume you will have found that by now.

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