Srho.ts and surrogate data obtained through
Simulated Annealing. The statistics Trho is based on the quadratic divergence between the nonparametric estimator of Srho
and the parametric estimator under the null hypothesis of a linear Gaussian process.Trho.test.SA(x, y, lag.max = 10, B = 100, plot = TRUE, quant = c(0.95, 0.99), bw = c("reference","mlcv", "lscv"), method =c("integral","summation"), maxpts=0, tol=1e-03, nlag=trunc(length(x)/4), Te=0.0015, RT=0.9, eps.SA=0.01, nsuccmax=30, nmax=300, che=100000)y is missing in the univariate case).trunc(N/4) where N is the number of observations.TRUE(the default) produces a plot of Trho together with confidence bands under the null hypothesis of linearity at 95% and 99%.Srho.ts.Srho.ts.Srho.ts.Srho.ts.surrogate.SA.surrogate.SA.surrogate.SA.surrogate.SA.surrogate.SA.surrogate.SA.surrogate.SA.lag.max elements containing Trho computed at each lag.call:"call": contains the call to the routine.call.h:"call": contains the call to the routine used for obtaining the surrogates or the bootstrap replicates under the null hypothesis."matrix": contains the quantiles of the surrogate distribution under the null hypothesis.test.type"character": contains a description of the type of test performed."list": contains the lags at which Trho exceeds the confidence bands at quant% under the null hypothesis."numeric": contains the bootstrap p-value for each lag."logical": TRUE if the stationary version is computed. Set to FALSE by default as only the non-stationary version is implemented."character": contains the data type."character": additional notes.lag.max Trho.test.SA computes a test for nonlinearity for time series based
on Srho.ts. The distribution under the null hypothesis of a linear Gaussian process is obtained through a generalization of surrogate data
methods. Surrogate time series are obtained through Simulated Annealing (SA). Sensible (N-dependent) defaults are derived for the parameters of the SA
algorithm, there should not be the need to change them.
Srho.ts, surrogate.SA, Trho.test.AR. See Trho.test.SA.p for the parallel version.## Not run:
# set.seed(1345)
# x <- arima.sim(n=120, model = list(ar=0.8));
# result <- Trho.test.SA(x, lag.max = 5, B = 10, bw='reference', method='integral')
# ## End(Not run)Run the code above in your browser using DataLab