| Financial Toolbox™ | ![]() |
y = nanvar(X) y = nanvar(X,1) y = nanvar(X,W) y = nanvar(X,W,DIM)
X | Financial times series object. |
W | Weight vector. |
DIM | Dimension along which the operation is conducted. |
nanvar for financial times series objects is based on the Statistics Toolbox™ function nanvar. See nanvar in the Statistics Toolbox documentation.
y = nanvar(X) returns the sample variance of the values in a financial time series object X, treating NaNs as missing values. y is the variance of the non-NaN elements of each series in X.
nanvar normalizes y by N – 1 if N > 1, where N is the sample size of the non-NaN elements. This is an unbiased estimator of the variance of the population from which X is drawn, as long as X consists of independent, identically distributed samples, and data are missing at random. For N = 1, y is normalized by N.
y = nanvar(X,1) normalizes by N and produces the second moment of the sample about its mean. nanvar(X, 0) is the same as nanvar(X).
y = nanvar(X,W) computes the variance using the weight vector W. The length of W must equal the length of the dimension over which nanvar operates, and its non-NaN elements must be nonnegative. Elements of X corresponding to NaN elements of Ware ignored.
y = nanvar(X,W,DIM) takes the variance along dimension DIM of X.
To compute nanvar:
f = fints((today:today+1)', [4 -2 1; 9 5 7])
f.series1(1) = nan;
f.series3(2) = nan;
nvar = nanvar(f)
nvar =
0 24.5000 0
nanmax, nanmean, nanmedian, nanmin, nanstd, var
![]() | nansum | negvolidx | ![]() |
| © 1984-2008- The MathWorks, Inc. - Site Help - Patents - Trademarks - Privacy Policy - Preventing Piracy - RSS |