Rènyi-Type Statistic Simulation
Simulates multiple realizations of the Rènyi-type statistic.
sim_Zn_stat(size, kn = function(n) { floor(sqrt(n)) }, use_kernel_var = FALSE, kernel = "ba", bandwidth = "and", n = 500, gen_func = rnorm, args = NULL, parallel = FALSE)
size |
Number of realizations to simulate |
kn |
A function returning a positive integer that is used in the definition of the Rènyi-type statistic effectively setting the bounds over which the maximum is taken |
use_kernel_var |
Set to |
kernel |
If character, the identifier of the kernel function as used in
the cointReg (see documentation for
|
bandwidth |
If character, the identifier of how to compute the bandwidth
as defined in the cointReg package (see
documentation for |
n |
The sample size for each realization |
gen_func |
The function generating the random sample from which the statistic is computed |
args |
A list of arguments to be passed to |
parallel |
Whether to use the foreach and doParallel packages to parallelize simulation (which needs to be initialized in the global namespace before use) |
This differs from sim_Zn()
in that the long-run variance is estimated
with this function, while sim_Zn()
assumes the long-run variance is
known. Estimation can be done in a variety of ways. If use_kernel_var
is set to TRUE
, long-run variance estimation using kernel-based
techniques will be employed; otherwise, a technique resembling standard
variance estimation will be employed. Any technique employed, though, will
account for the potential break points, as described in
Rice et al. (). See the documentation for
stat_Zn
for more details.
The parameters kernel
and bandwidth
control parameters for
long-run variance estimation using kernel methods. These parameters will be
passed directly to stat_Zn
.
A vector of simulated realizations of the Rènyi-type statistic
Andrews DWK (1991). “Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation.” Econometrica, 59(3), 817-858.
Rice G, Miller C, Horváth L (????). “A new class of change point test of Rényi type.” in-press.
CPAT:::sim_Zn_stat(100) CPAT:::sim_Zn_stat(100, kn = function(n) {floor(log(n))}, use_kernel_var = TRUE, gen_func = CPAT:::rchangepoint, args = list(changepoint = 250, mean2 = 1))
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