Trho.test.AR.p {tseriesEntropy} | R Documentation |
Entropy Tests For Nonlinearity In Time Series - Parallel Version
Description
Entropy test of nonlinearity for time series based
on Srho.ts
and surrogate data obtained through
the sieve bootstrap (AR modeling). The parallel version requires parallel
.
Usage
Trho.test.AR(x, y, lag.max = 10, B = 100, plot = TRUE, quant = c(0.95, 0.99),
bw = c("reference", "mlcv", "lscv", "scv", "pi"), bdiag=TRUE,
method = c("integral", "summation"), tol = 0.001, order.max = NULL,
fit.method=c("yule-walker", "burg", "ols", "mle", "yw"), smoothed = TRUE,...)
## Parallel version
Trho.test.AR.p(x, y, lag.max = 10, B = 100, plot = TRUE, quant = c(0.95, 0.99),
bw = c("reference", "mlcv", "lscv", "scv", "pi"), bdiag=TRUE,
method = c("integral", "summation"), tol = 0.001, order.max = NULL,
fit.method=c("yule-walker", "burg", "ols", "mle", "yw"), smoothed = TRUE,
nwork=detectCores(),...)
Arguments
x , y |
univariate numeric time series object or numeric vectors ( |
lag.max |
maximum lag at which to calculate Trho; the default is 10. |
B |
number of surrogate time series. |
plot |
logical. If |
quant |
quantiles to be specified for the computation of the significant lags and the plot of confidence bands. Up to 2 quantiles can be specified. Defaults are 95% and 99%. |
bw |
see |
bdiag |
see |
method |
see |
tol |
see |
order.max |
see |
fit.method |
see |
smoothed |
logical. If |
nwork |
number of workers/processes to be used in parallel environments. |
... |
further arguments, typically passed to |
Details
For each lag from 1 to lag.max
Trho.test.AR
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 the sieve bootstrap.
The routine requires the package parallel to spawn multiple workers.
Value
An object of class "Srho.test", which is a list with the following elements:
.Data |
vector of |
call: |
Object of class |
call.h: |
Object of class |
quantiles |
Object of class |
test.type |
Object of class |
significant.lags |
Object of class |
p.value |
Object of class |
lags |
integer vector that contains the lags at which Trho is computed. |
stationary |
Object of class |
data.type |
Object of class |
notes |
Object of class |
Author(s)
Simone Giannerini<simone.giannerini@unibo.it>
References
Giannerini S., Maasoumi E., Bee Dagum E., (2015), Entropy testing for nonlinear serial dependence in time series, Biometrika, 102(3), 661–675 doi:10.1093/biomet/asv007.
See Also
See Also Srho.ts
, surrogate.AR
, surrogate.ARs
, Trho.test.AR
.
Examples
## Not run:
# modify nwork to match the number of available cores
set.seed(13)
b <- 100
x <- arima.sim(n=120, model = list(ar=0.8));
result <- Trho.test.AR.p(x, lag.max = 5, B=b, nwork=2)
## ** Compare timings **
system.time(Trho.test.AR.p(x,lag.max = 5,B=b, nwork=4))
system.time(Trho.test.AR(x, lag.max = 5,B=b))
## End(Not run)