11 October 2024
11 October 2024
Function |
Action |
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Singular Value Decomposition, divide-and-conquer algorithm; considered the fastest among other SVD algorithms (lapack function GESDD). |
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Singular Value Decomposition, QR algorithm; considered a classical SVD algorithm (lapack function GESVD). |
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Singular Value Decomposition, QR with pivoting algorithm (lapack function GESVDQ). |
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Singular Value Decomposition, bisection algorithm (lapack function GESVDX). |
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Singular Value Decomposition, Jacobi high-level algorithm (lapack function GEJSV). |
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Singular Value Decomposition, Jacobi low-level algorithm (lapack function GESVJ). The method computes small singular values and their singular vectors with much greater accuracy than other SVD routines in certain cases. |
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Singular Value Decomposition, divide-and-conquer algorithm for bidiagonal matrices (lapack function BDSVDX). |
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Singular Value Decomposition, bisection algorithm for bidiagonal matrices (lapack function BDSVDX). |
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Compute eigenvalues and eigenvectors of a regular square matrix using the classical algorithm (lapack function GEEV). |
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Compute eigenvalues and eigenvectors of a symmetric or Hermitian (complex conjugate) matrix using the divide-and-conquer algorithm (lapack functions SYEVD, HEEVD). |
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A method function for calculating the relative contributions of spectral components based on their eigenvalues |
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A method function for calculating reconstructed and predicted data using spectral components of the input time series. |
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A method function for calculating reconstructed components of the input time series and their contributions. |
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A method function for calculating the reconstructed time series using the first component_count components. |