Table Of Contents

Measures of Spread (Covariance Matrix) (G Dataflow)

Version:
    Last Modified: January 9, 2017

    Computes the covariance matrix of a sequence.

    connector_pane_image
    datatype_icon

    x

    The input sequence. Each column of x represents one vector of observed samples from one variable. Each row of x represents an observation from each variable.

    datatype_icon

    error in

    Error conditions that occur before this node runs. The node responds to this input according to standard error behavior.

    Default: No error

    datatype_icon

    covariance matrix v

    Covariance matrix of the input sequence.

    If x is an n-by-m 2D array, then the covariance matrix is a square m-by-m matrix.

    datatype_icon

    mean vector

    Mean of each column variable in the input sequence.

    datatype_icon

    error out

    Error information. The node produces this output according to standard error behavior.

    Algorithm for Computing the Covariance Matrix

    Given m vectors of observed samples where the ith column contains the variate xi, the covariance matrix is defined as:

    v i j = ( x i μ i ) ( x j μ j )

    where μ i is the mean of variate xi.

    Each element vij of covariance matrix v is the covariance between variates xi and xj. The diagonal of covariance matrix v contains the standard variances of each xi variate.

    mean vector returns the computed mean of each variate as shown by the following equation:

    mean vector i = μ i

    Where This Node Can Run:

    Desktop OS: Windows

    FPGA: Not supported


    Recently Viewed Topics