iossa.result | R Documentation |
Various routines to print Iterative Oblique SSA results
## S3 method for class 'iossa.result'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'iossa.result'
summary(object, digits = max(3, getOption("digits") - 3), ...)
x , object |
object of class ‘iossa.result’ or ‘ossa’ |
digits |
integer, used for number formatting |
... |
further arguments passed to method |
An object of class ‘iossa.result’ is a list with the following fields:
logical, whether algorithm has been converged
the number of OSSA iterations
numeric vector with two elements, condition numbers of the final column and row inner products
numeric vector, proportions of high rank components contribution for each of initial series (denotes how well the series is approximated by a series of finite rank)
numeric vector, proportions of high rank components contribution for each of final series
W-correlation matrix of the initial nested decomposition
W-correlations matrix of the final nested decomposition
oblique W-correlation matrix (see owcor
)
of the final nested decomposition
list of initial series (reconstructed initial nested decomposition)
Iterative O-SSA procedure parameters
Golyandina N. and Shlemov A. (2015): Variations of Singular Spectrum Analysis for separability improvement: non-orthogonal decompositions of time series, Statistics and Its Interface. Vol.8, No 3, P.277-294. https://arxiv.org/abs/1308.4022
Rssa
for an overview of the package, as well as,
iossa
,
owcor
,
summary.ssa
.
# Separate three non-separable sines with different amplitudes
N <- 150
L <- 70
omega1 <- 0.05
omega2 <- 0.06
omega3 <- 0.07
F <- 4*sin(2*pi*omega1 * (1:N)) + 2*sin(2*pi*omega2 * (1:N)) + sin(2*pi*omega3 * (1:N))
s <- ssa(F, L)
ios <- iossa(s, nested.groups = list(1:2, 3:4, 5:6), kappa = NULL, maxiter = 100, tol = 1e-3)
print(ios)
print(ios$iossa.result)
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