Plot a csFSS object.

Description

Produces two types of plot from the information in a csFSS object, such as that returned by findstysols.

Usage

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## S3 method for class 'csFSS'
plot(x, solno = NULL, ALLplotclust = TRUE, ALLplotscale = TRUE, sollabels=TRUE,
    SNinc = 0, ...)

Arguments

x

The csFSS object you wish to produce plots for.

solno

If missing then the plot produces plots that show information on all solutions at once, first in a scatter plot, then in a dendrogram. If provided then the plot produces information on that specific solution.

ALLplotclust

If TRUE then the dendrogram is plotted, if FALSE it is not.

ALLplotscale

If TRUE then the two-dimensional scaling solution is plotted. If FALSE, it is not.

sollabels

If TRUE then solution numbers are plotted on the scaling plot, if produced.

SNinc

An argument passed to the LCTSres function if called. When plotting add an increment on where to start looking at the time series/solutions from.

...

Other arguments passed to plot.

Details

This function can produce either a scatterplot, which indicates the two-dimensional scaling picture of the optimization solution sets, or a dendrogram showing putative clustering of solutions. In both cases it is a plot considering ALL solutions at once. These plots are delegated to the plot.csFSSgr function.

If the argument solno is provided then plots are produced which show information on a single solution. This plot is delegated to the LCTSres function.

Value

None.

Author(s)

G.P.Nason

References

Cardinali, A. and Nason, Guy P. (2013) Costationarity of Locally Stationary Time Series Using costat. Journal of Statistical Software, 55, Issue 1.

Cardinali, A. and Nason, G.P. (2010) Costationarity of locally stationary time series. J. Time Series Econometrics, 2, Issue 2, Article 1.

See Also

findstysols, LCTSres, plot.csFSSgr, print.csFSS, summary.csFSS

Examples

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#
# Create dummy data
#
x1 <- rnorm(32)
y1 <- rnorm(32)
#
# Find stationary combinations
# Note: we don't run this example in installation/package formation as
# it takes a long time. However, this precise command IS run in
# the help to findstysols
#
## Not run: ans <- findstysols(Nsims=100, tsx=x1, tsy=y1)
#
# Produce dendrogram
#
## Not run: plot(ans)
#
# Produce four pictures relating to solution 3 (can also do
# par(mfrow=c(2,2)) to make a nice 4 plot on one page.)
#
## Not run: plot(ans, solno=3)
#solno is  3 
#3 
#1: 

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