standard deviation (ignoring the NANs).
s=nanstdev(x)
s=nanstdev(x,'r') or m=nanstdev(x,1)
s=nanstdev(x,'c') or m=nanstdev(x,2)
:x real or complex vector or matrix :
This function computes the standard deviation of the values of a vector or matrix x (ignoring the NANs).
For a vector or a matrix x, s=nanstdev(x) returns in the scalar s the standard deviation of all the entries of x (ignoring the NANs).
s=nanstdev(x,’r’) (or, equivalently, s=nanstdev(x,1)) is the rowwise standard deviation. It returns in each entry of the row vector s the standard deviation of each column of x (ignoring the NANs).
s=nanstdev(x,’c’) (or, equivalently, s=nanstdev(x,2)) is the columnwise standard deviation. It returns in each entry of the column vector s the standard deviation of each row of x (ignoring the NANs).
In Labostat, NAN values stand for missing values in tables.
x=[0.2113249 0.0002211 0.6653811;
0.7560439 %nan 0.6283918;
0.3 0.2 0.5 ];
s=nanstdev(x)
s=nanstdev(x,'r')
s=nanstdev(x,'c')
Wonacott, T.H. & Wonacott, R.J.; Introductory Statistics, fifth edition, J.Wiley & Sons, 1990.