A Collection of Methods for Singular Spectrum Analysis
Group elementary series using periodogram
Classical `Barbara' image (color, wide)
Perform bootstrap SSA forecasting of the series
Cadzow Iterations
Calculate Factor Vector(s)
Cleanup of all cached data from SSA objects
Cloning of SSA objects
Ratio of complete lag vectors in dependence on window length
Group Elementary Series Using W-correlation Matrix
Perform SSA Decomposition
ESPRIT-based O-SSA nested decomposition
Perform SSA forecasting of series
Nested Filter-adjusted O-SSA decomposition
Calculate Frobenius correlations of the component matrices
Perform SSA gapfilling via forecast
Group Elementary Series
Hankel matrices operations.
Hankel with Hankel block matrices operations.
Calculate the heterogeneity matrix.
Perform SSA gapfilling via iterative reconstruction
Iterative O-SSA nested decomposition
Summary of Iterative O-SSA results
Calculate the min-norm Linear Recurrence Relation
Calculate generalized (oblique) W-correlation matrix
Estimate periods from (set of) eigenvectors
Plot SSA object
Plot the results of SSA reconstruction
Calculates and caches elementary components inside SSA object
Perform a series reconstruction
Obtain the residuals from SSA reconstruction
Perform recurrent SSA forecasting of the series
A collection of methods for singular spectrum analysis
Input Data Formats Used by SSA Routines
Properties of SSA object
SSA methods and capabilities check
Create a new SSA object
Summarize Gaps in a Series
Toeplitz matrices operations.
Perform vector SSA forecasting of the series
Calculate the W-correlation matrix
Calculate Weighted Norm of series
Methods and tools for Singular Spectrum Analysis including decomposition, forecasting and gap-filling for univariate and multivariate time series. General description of the methods with many examples can be found in the book Golyandina (2018, <doi:10.1007/978-3-662-57380-8>). See 'citation("Rssa")' for details.