mssa (pyleoclim.utils.decomposition.mssa)

pyleoclim.utils.decomposition.mssa(ys, M=None, nMC=0, f=0.3)[source]

Multi-channel singular spectrum analysis analysis

Multivariate generalization of SSA [2], using the original algorithm of [1]. Each variable is called a channel, hence the name.

Parameters

ys (array) – multiple time series (dimension: length of time series x total number of time series)
M (int) – window size (embedding dimension, default: 10% of the length of the series)
nMC (int) – Number of iteration in the Monte-Carlo process [default=0, no Monte Carlo process]
f (float) – fraction (0<f<=1) of good data points for identifying significant PCs [f = 0.3]

Returns

res – Containing:

eigvals : array of eigenvalue spectrum
eigvals05 : The 5% percentile of eigenvalues
eigvals95 : The 95% percentile of eigenvalues
PC : matrix of principal components (2D array)
RC : matrix of RCs (nrec,N,nrec*M) (2D array)

Return type

dict

References

[1]_ Vautard, R., and M. Ghil (1989), Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series, Physica D, 35, 395–424.

[2]_ Jiang, N., J. D. Neelin, and M. Ghil (1995), Quasi-quadrennial and quasi-biennial variability in the equatorial Pacific, Clim. Dyn., 12, 101-112.