Produce vectors of mean and dispersion values for generating piecewise stationary time series.
testSignal(
model = c("custom", "blocks", "fms", "mix", "stairs10", "teeth10")[1],
lengths = NULL,
means = NULL,
sds = NULL
)a list containing the following entries:
mu_t mean vector of piecewise stationary model time series
sigma_t deviation scaling vector of piecewise stationary model time series
a string indicating from which model a realisation is to be generated;
possible values are "custom" (for user-specified model
using lengths, means and sds), and
"blocks", "fms", "mix", "stairs10", "teeth10" (for the referenced test signals)
use iff model = "custom"; an integer vector for the lengths of the piecewise stationary segments
use iff model = "custom"; a numeric vector for the means of the piecewise stationary segments
use iff model = "custom"; a numeric vector for the deviation scaling of the piecewise stationary segments.
See Appendix B in the reference for details about the test signals.
P. Fryzlewicz (2014) Wild Binary Segmentation for Multiple Change-Point Detection. The Annals of Statistics, Volume 42, Number 6, pp. 2243-2281.