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object StatVector

The StatVector companion object extends statistics vector operations to matrices.

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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  5. def center(x: MatrixD, mu_x: VectorD): MatrixD

    Center the input matrix 'x' to zero mean, column-wise, by subtracting the mean.

    Center the input matrix 'x' to zero mean, column-wise, by subtracting the mean.

    x

    the input matrix to center

    mu_x

    the vector of column means of matrix x

  6. def clone(): AnyRef
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  7. def corr(x: MatrixD): MatrixD

    Return the correlation matrix for the columns of matrix 'x'.

    Return the correlation matrix for the columns of matrix 'x'. Note: sample vs. population results in essentailly the same values.

    x

    the matrix whose column columns correlations are sought

  8. def corrMat(y: VectorD): MatrixD

    Return the first-order auto-regressive correlation matrix for vector (e.g., time series) 'y'.

    Return the first-order auto-regressive correlation matrix for vector (e.g., time series) 'y'.

    y

    the vector whose auto-regressive correlation matrix is sought

    See also

    halweb.uc3m.es/esp/Personal/personas/durban/esp/web/notes/gls.pdf

  9. def cov(x: MatrixD): MatrixD

    Return the sample covariance matrix for the columns of matrix 'x'.

    Return the sample covariance matrix for the columns of matrix 'x'.

    x

    the matrix whose column covariances are sought

  10. def covMat(y: VectorD): MatrixD

    Return the first-order auto-regressive covariance matrix for vector (e.g., time series) 'y'.

    Return the first-order auto-regressive covariance matrix for vector (e.g., time series) 'y'.

    y

    the vector whose auto-regressive covariance matrix is sought

    See also

    halweb.uc3m.es/esp/Personal/personas/durban/esp/web/notes/gls.pdf

  11. final def eq(arg0: AnyRef): Boolean
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  12. def equals(arg0: Any): Boolean
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  13. def finalize(): Unit
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  14. final def getClass(): Class[_]
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  15. def hashCode(): Int
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  16. final def isInstanceOf[T0]: Boolean
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  17. def mean(x: MatrixD): VectorD

    Return the mean vector containing the means of each column of matrix 'x'.

    Return the mean vector containing the means of each column of matrix 'x'.

    x

    the matrix whose column means are sought

  18. final def ne(arg0: AnyRef): Boolean
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  19. final def notify(): Unit
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  20. final def notifyAll(): Unit
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  21. def pcov(x: MatrixD): MatrixD

    Return the population covariance matrix for the columns of matrix 'x'.

    Return the population covariance matrix for the columns of matrix 'x'.

    x

    the matrix whose column columns covariances are sought

  22. final def synchronized[T0](arg0: ⇒ T0): T0
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  23. def toString(): String
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  24. final def wait(): Unit
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  25. final def wait(arg0: Long, arg1: Int): Unit
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  26. final def wait(arg0: Long): Unit
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