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# nanvar

Variance ignoring NaNs

## Syntax

```y = nanvar(X)
y = nanvar(X,1)
y = nanvar(X,W)
y = nanvar(X,W,DIM)
```

## Arguments

 X Financial times series object. W Weight vector. DIM Dimension along which the operation is conducted.

## Description

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 N1 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.

## Examples

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
```