Computes the covariance matrix or correlation matrix of a multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.


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Inputs/Outputs

  • c1dmsdt.png Xt —

    Xt specifies the multivariate (vector) time series.

  • cu16.png weighting —

    weighting specifies which variance to calculate. Options include Sample and Population. The default is Sample (N-1).

  • cerrcodeclst.png error in (no error) —

    error in describes error conditions that occur before this node runs. This input provides standard error in functionality.

  • cbool.png normalized? (F) —

    normalized? specifies to normalize the results into a covariance matrix, where the nondiagonal elements are close to one. The default is FALSE.

  • i2ddbl.png covariance —

    covariance returns the calculated covariance matrix of the multivariate (vector) time series.

  • ierrcodeclst.png error out —

    error out contains error information. This output provides standard error out functionality.

    • TSA Covariance Details

    When normalized? is FALSE, this VI calculates the covariance matrix for a multivariate time series m according to the following equation:

    xi, as a row vector, is the ith channel time series. mi is the arithmetic mean of xi. The dimension of the covariance matrix is mxm. w is weighting. w=n when weighting is set to Population. w=n-1 when weighting is set to Sample.

    When normalized? is TRUE, this VI calculates the correlation coefficient matrix according to the following equation:

    The above operation is equivalent to unifying each channel xi with zero mean and unit energy and then calculating the covariance matrix of the unified multivariate time series.