Description Usage Arguments Details Value Author(s) References See Also Examples
A data stream generator based on the three-dimensional Rössler Attractor.
1 2 3 |
N |
Determines the data stream length. |
start.x |
Determines the initial condition. |
parms |
The set of parameters σ, ρ, and β for the Lorenz' three-dimensional equation. |
dt |
|
warming.up.num |
Number of observations for warming up the attractor. |
range |
|
noise.type |
Type of the noise ("None", "Uniform", "Normal") |
noise.parms |
A list for generating the noise. |
NLDSD_LorenzAttractor
creates a data stream based on the three-dimensional Lorenz Attractor:
x_{t+1} = -y_t - z_t, y_{t+1} = x_t + a y_t, z_{t+1} = b + z_t (x_t + c),
in which the parameters a, b, and c change the data behavior. Traditionally, they are set to 0.15, 0.2, and 10 respectively, producing a chaotic data. Other values may be used, as shown in Wikipedia.
In this code, only the variable x_t is returned.
Returns a NLDSD_RosslerAttractor
object (subclass of NLDSD
) which is a list of the defined params.
Fausto Guzzo da Costa
https://en.wikipedia.org/wiki/Rössler_attractor
1 2 3 4 5 6 7 8 9 10 11 12 13 | # create a data stream with 10,000 observations based on a Rossler Attractor
# and plot it
stream1 <- NLDSD_RosslerAttractor(N=10000)
plot(stream1)
# create a data stream with 10,000 observations based on a Rossler Attractor
# with noise produced by a Normal distribution
# with mean=0 and std=0.1
# and plot it
stream2 <- NLDSD_RosslerAttractor(N=10000, noise.type="Normal",
noise.parms=list(mean=0, sd=0.1))
plot(stream2)
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