clusterify: Group Elementary Series Using W-correlation Matrix

In Rssa: A Collection of Methods for Singular Spectrum Analysis

Group Elementary Series Using W-correlation Matrix

Description

Group elemenatry series automatically via the hierarchical clustering with w-correlation matrix as a proximity matrix

Usage

## S3 method for class 'ssa'
grouping.auto.wcor(x, groups, nclust = length(groups) / 2, ...)

Arguments

x	SSA object
groups	list of numeric vectors, indices of elementary components used for reconstruction
nclust	integer, desired number of output series
...	further arguments passed to hclust

Details

Standard hclust routine is used to perform the grouping of the elementary components. See Algorithm 2.15 in Golyandina et al (2018) for details.

Value

List of integer vectors holding the indices of the elementary components forming each grouped objects

References

Golyandina N., Korobeynikov A., Zhigljavsky A. (2018): Singular Spectrum Analysis with R. Use R!. Springer, Berlin, Heidelberg.

See Also

hclust, wcor

Examples

# Decompose 'co2' series with default parameters
s <- ssa(co2)
# Form 3 series from the initial 6 ones:
lst <- grouping.auto(s, grouping.method = "wcor",
                     groups = 1:6, nclust=3)
# Automatic grouping:
print(lst)
plot(lst)
# Check separability
w <- wcor(s, groups = lst)
plot(w)

Rssa documentation built on Sept. 11, 2024, 7:20 p.m.