turns | R Documentation |
Extracts and analyzes turning points of an univariate
"timeSeries"
object.
turns(x, ...)
turnsStats(x, doplot = TRUE)
x |
an univariate |
... |
optional arguments passed to the function |
doplot |
a logical flag, should the results be plotted? By default TRUE. |
The function turns
determines the number and the positions of
extrema (turning points, either peaks or pits) in a regular time
series.
The function turnsStats
calculates the quantity of information
associated with the observations in this series, according to
Kendall's information theory.
The functions are borrowed from the contributed R package
pastecs
and made ready for working together with univariate
timeSeries
objects. You need not to load the R package
pastecs
, the code parts we need here are builtin in the
timeSeries
package.
We have renamed the function turnpoints
to turns
to
distinguish between the original function in the contributed R package
pastecs
and our Rmetrics function wrapper.
For further details please consult the help page from the contributed
R package pastecs
.
for turns
, an object of class timeSeries
.
for turnsStats
, an object of class turnpoints
with the
following entries:
data |
The dataset to which the calculation is done. |
n |
The number of observations. |
points |
The value of the points in the series, after elimination of ex-aequos. |
pos |
The position of the points on the time scale in the series (including ex-aequos). |
exaequos |
Location of exaequos (1), or not (0). |
nturns |
Total number of turning points in the whole time series. |
firstispeak |
Is the first turning point a peak (TRUE), or not (FALSE). |
peaks |
Logical vector. Location of the peaks in the time series without ex-aequos. |
pits |
Logical vector. Location of the pits in the time series without ex-aequos. |
tppos |
Position of the turning points in the initial series (with ex-aequos). |
proba |
Probability to find a turning point at this location. |
info |
Quantity of information associated with this point. |
Frederic Ibanez and Philippe Grosjean for code from the contributed R
package pastecs
and Rmetrics for the function wrapper.
Ibanez, F., 1982, Sur une nouvelle application de la theorie de l'information a la description des series chronologiques planctoniques. J. Exp. Mar. Biol. Ecol., 4, 619–632
Kendall, M.G., 1976, Time Series, 2nd ed. Charles Griffin and Co, London.
## Load Swiss Equities Series -
SPI.RET <- LPP2005REC[, "SPI"]
head(SPI.RET)
## Cumulate and Smooth the Series -
SPI <- smoothLowess(cumulated(SPI.RET), f=0.05)
plot(SPI)
## Plot Turn Points Series -
SPI.SMOOTH <- SPI[, 2]
tP <- turns(SPI.SMOOTH)
plot(tP)
## Compute Statistics -
turnsStats(SPI.SMOOTH)
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