object StatVector
The StatVector companion object extends statistics vector operations to matrices
and convenience functions on vectors.
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- def acorr(y: VectoD): Double
Compute the '1'-lag auto-correlation of 'self' vector.
Compute the '1'-lag auto-correlation of 'self' vector. Assumes a stationary vector, if not its an approximation.
- y
the vector whose auto-correlation is sought
- def acorrz(z: VectoD): Double
Compute the '1'-lag auto-correlation of 'self' vector.
Compute the '1'-lag auto-correlation of 'self' vector. Assumes a zero-centered, stationary vector, if not its an approximation.
- z
the zero-centered vector whose auto-correlation is sought
- def acov(y: VectoD): Double
Compute the '1'-lag auto-covariance of 'self' vector.
Compute the '1'-lag auto-covariance of 'self' vector.
- y
the vector whose auto-covariance is sought
- def acovz(z: VectoD): Double
Compute the '1'-lag auto-covariance of 'self' vector.
Compute the '1'-lag auto-covariance of 'self' vector.
- z
the zero-centered vector whose auto-covariance is sought
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- def center(x: MatriD, mu_x: VectoD): MatriD
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
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- def corr(x: MatriD): MatriD
Return the correlation matrix for the columns of matrix 'x'.
Return the correlation matrix for the columns of matrix 'x'. If either variance is zero (column i, column j), will result in Not-a-Number (NaN), return one if the vectors are the same, or -0 (indicating undefined). Note: sample vs. population results in essentailly the same values.
- x
the matrix whose column-column correlations are sought
- See also
the related 'cos' function.
- def corrMat(y: VectoD): MatriD
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
- def cos(x: MatriD): MatriD
Return the cosine similarity matrix for the columns of matrix 'x'.
Return the cosine similarity matrix for the columns of matrix 'x'. If the vectors are centered, will give the correlation.
- x
the matrix whose column-column cosines are sought
- See also
stats.stackexchange.com/questions/97051/building-the-connection-between-cosine-similarity-and-correlation-in-r
- def cov(x: MatriD): MatriD
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
- def covMat(y: VectoD): MatriD
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
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- def pcov(x: MatriD): MatriD
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
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