PCA

[Tathagata Ghose]

Hello,

I have another question. I often have to extract the Principal Components (using Principal Component Analysis (PCA)) from a number of selected data series.

I know that Flexpro has a plethora of Eigen decomposition related functions. But, since PCA can be called different things, I’m wondering whether Flexpro already does PCA under a different function name. If not, what would be the simplest few lines of matrix commands to extract the PCs?

Regards
Tatha

[Tathagata Ghose]

Hello,

I have another question. I often have to extract the Principal Components (using Principal Component Analysis (PCA)) from a number of selected data series.

I know that Flexpro has a plethora of Eigen decomposition related functions. But, since PCA can be called different things, I’m wondering whether Flexpro already does PCA under a different function name. If not, what would be the simplest few lines of matrix commands to extract the PCs?

Regards
Tatha

[Bernhard Kantz]

Option Spectral Analysis:
The identification, isolation, and reconstruction of signal components via eigendecomposition is known by a variety of names. “Singular Spectral Analysis”, “Principal Component Analysis”, and “Eigenfiltering” are common. FlexPro exclusively uses the “Eigendecomposition” designation since it represents a more precise description of the numeric method.

Eigendecompositions are used in various algorithms throughout FlexPro. They are the principal methodology in the:
– Eigen (MUSIC, EV) Spectral Estimator
Eigendecompositions are also intrinsically a part of all FlexPro procedures that include SVD (singular value decomposition) methods:
– AR (AutoRegressive) Spectral Estimator
– ARMA (AutoRegressive Moving Average) Spectral Estimator

Option Statistics:
You can caluclate the Correlation matrix and the Covariance matrix. But there is no implicit function to calculate the principal components of a data matrix.

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