pca.tpdm: Principal Component Analysis for TPDM
In ExtrPatt: Spatial Dependencies and Indices for Extremes
pca.tpdm R Documentation
Principal Component Analysis for TPDM
Description
Calculates principal component analysis (PCA) of given TPDM
Usage
pca.tpdm(Sigma, data)
Arguments
Sigma
A n x n data array, containing the TPDM, can be output of est.tpdm.
data
A t x n dimensional, numeric Data-matrix with t: Number of time steps and n: Number of grid points/stations.
Value
list containing
pc: The Principal Components of TPDM
basis: The Eigenvectors of TPDM
extremal.basis: The Eigenvectors of TPDM but transformed in positive reals with trans
Author(s)
Yuing Jiang, Dan Cooley
References
Jiang & Cooley (2020) <doi:10.1175/JCLI-D-19-0413.1>
ExtrPatt documentation built on Nov. 8, 2023, 1:09 a.m.
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| pca.tpdm | R Documentation |
Principal Component Analysis for TPDM
Description
Calculates principal component analysis (PCA) of given TPDM
Usage
pca.tpdm(Sigma, data)
Arguments
Sigma |
A n x n data array, containing the TPDM, can be output of est.tpdm. |
data |
A t x n dimensional, numeric Data-matrix with t: Number of time steps and n: Number of grid points/stations. |
Value
list containing
pc: The Principal Components of TPDM
basis: The Eigenvectors of TPDM
extremal.basis: The Eigenvectors of TPDM but transformed in positive reals with trans
Author(s)
Yuing Jiang, Dan Cooley
References
Jiang & Cooley (2020) <doi:10.1175/JCLI-D-19-0413.1>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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