sim_hs_stat {CPAT}

Hidalgo-Seo Statistic Simulation

Description

Simulates multiple realizations of the Hidalgo-Seo statistic.

Usage

sim_hs_stat(size, corr = TRUE, gen_func = rnorm, args = NULL,
  n = 500, parallel = FALSE, use_kernel_var = FALSE, kernel = "ba",
  bandwidth = "and")

Arguments

size

Number of realizations to simulate

corr

Whether long-run variance should be computed under the assumption of correlated residuals

gen_func

The function generating the random sample from which the statistic is computed

args

A list of arguments to be passed to gen_func

n

The sample size for each realization

parallel

Whether to use the foreach and doParallel packages to parallelize simulation (which needs to be initialized in the global namespace before use)

use_kernel_var

Set to TRUE to use kernel-based long-run variance estimation (FALSE means this is not employed); TODO: NOT CURRENTLY IMPLEMENTED

kernel

If character, the identifier of the kernel function as used in the cointReg (see documentation for cointReg::getLongRunVar); if function, the kernel function to be used for long-run variance estimation (default is the Bartlett kernel in cointReg); this parameter has no effect if use_kernel_var is FALSE; TODO: NOT CURRENTLY IMPLEMENTED

bandwidth

If character, the identifier of how to compute the bandwidth as defined in the cointReg package (see documentation for cointReg::getLongRunVar); if function, a function to use for computing the bandwidth; if numeric, the bandwidth to use (the default behavior is to use the Andrews (1991) method, as used in cointReg); this parameter has no effect if use_kernel_var is FALSE; TODO: NOT CURRENTLY IMPLEMENTED

Details

If corr is TRUE, then the residuals of the data-generating process are assumed to be correlated and the test accounts for this in long-run variance estimation; see the documentation for stat_hs for more details. Otherwise, the sample variance is the estimate for the long-run variance, as described in Hidalgo and Seo (2013).

Value

A vector of simulated realizations of the Hidalgo-Seo statistic

References

Andrews DWK (1991). “Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation.” Econometrica, 59(3), 817-858.

Hidalgo J, Seo MH (2013). “Testing for structural stability in the whole sample.” Journal of Econometrics, 175(2), 84 - 93. ISSN 0304-4076, doi: 10.1016/j.jeconom.2013.02.008, http://www.sciencedirect.com/science/article/pii/S0304407613000626.

Examples

CPAT:::sim_hs_stat(100)
CPAT:::sim_hs_stat(100, gen_func = CPAT:::rchangepoint, 
                   args = list(changepoint = 250, mean2 = 1))