Description Usage Arguments Value Author(s) References See Also Examples
The function simulates a surrogate (artificial) time series based on the defined properties. See Forkel et al. 2013 for a description how time series are simulated with this function.
1 2 3 4 5 6 7 |
M |
mean of the time series |
Tslope |
slope of the trend in each time series segment. |
Isd |
standard deviation of the annual mean values (inter-annual variability) |
Irange |
range of the annual mean values (inter-annual variability) |
Srange |
range of the seasonal cycle (seasonal amplitude) |
Rsd |
standard deviation of short-term anomalies |
Rrange |
range of short-term anomalies |
breaks |
position of the breakpoints in the time series. You should specify one more slope than breakpoint. |
abrupt |
Should the trend at the breakpoints change |
n |
length of the time series |
start |
beginning of the time series (i.e. the time of the first observation). The default is c(1982, 1), i.e. January 1982 which is the usual |
freq |
The frequency of observations. The default is 12 for monthly observations. Use 24 for bi-monthly observations, 365 for daily observations or 1 for annual observations. See |
The function returns multiple time series of class ts
with the following components: total time series, mean, trend component, inter-annual variability component, seasonal component, short-term component.
Matthias Forkel <matthias.forkel@tu-dresden.de> [aut, cre]
Forkel, M., N. Carvalhais, J. Verbesselt, M. Mahecha, C. Neigh and M. Reichstein (2013): Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology. - Remote Sensing 5.
1 2 3 4 5 6 7 8 9 10 11 12 13 | # simulate artificial time series
x <- SimTs(M=0.4, Tslope=0.0008, Isd=0.015, Irange=0.03, Srange=0.5, Rsd=0.05,
Rrange=0.1, breaks=NULL, abrupt=TRUE, n=360, start=c(1982, 1), freq=12)
plot(x)
x <- SimTs(M=0.35, Tslope=c(0.002, -0.0015), Isd=0.015, Irange=0.03, Srange=0.5,
Rsd=0.05, Rrange=0.1, breaks=120, abrupt=TRUE, n=360, start=c(1982, 1), freq=12)
plot(x)
x <- SimTs(M=0.4, Tslope=c(0.003, -0.001, 0), Isd=0.03, Irange=0.08, Srange=0.3,
Rsd=0.06, Rrange=0.2, breaks=c(100, 210), abrupt=FALSE,
n=360, start=c(1982, 1), freq=12)
plot(x)
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