Simulates the asymptotic null distribution of the statistic of
radf_sign. By Theorem 2 of Harvey, Leybourne & Zu (2020), this
distribution does not depend on the volatility process at all (exact
invariance). Like radf_tt_cv, and unlike radf_wb_cv,
it therefore does not have to be recomputed for each dataset. A large n
with the default nrep approximates the T -> Inf limit of the
paper.
Arguments
- n
A positive integer. The sample size.
- minw
A positive integer. The minimum window size (default = \((0.01 + 1.8/\sqrt{T})T\), where T denotes the sample size).
- nrep
A positive integer. The number of Monte Carlo simulations.
- seed
An object specifying if and how the random number generator (rng) should be initialized. It is either NULL or an integer, which is passed to
set.seedbefore the simulation. If you set it, the value is saved as the "seed" attribute of the returned value. The default, NULL, leaves the state of the rng unchanged and returns .Random.seed as the "seed" attribute. Results are reproducible across the parallel and the non-parallel option when you use the same seed.
Value
An object of class radf_cv/sign_cv/mc_cv with
the same structure as radf_mc_cv.
Details
You can check sadf_cv (single-supremum, r1 = 0 fixed) against the
asymptotic (T = Inf) sPWY values in Table 1 of the paper. For
minw/n = 0.1, the values at (10\
gsadf_cv (double-supremum) corresponds to the sPSY row: (2.933, 3.180,
3.655).
![[Experimental]](figures/lifecycle-experimental.svg)
References
Harvey, D. I., Leybourne, S. J., & Zu, Y. (2020). Sign-based unit root tests for explosive financial bubbles in the presence of deterministically time-varying volatility. Econometric Theory, 36(1), 122-169.
See also
Other critical values:
radf_common_cv(),
radf_mc_cv(),
radf_recovery_cv(),
radf_sb_cv(),
radf_sbz_cv(),
radf_sign_dm_cv(),
radf_tt_cv(),
radf_wb_cv(),
radf_wb_ps_cv()
Examples
# \donttest{
cv <- radf_sign_cv(n = 200, minw = 20)
tidy(cv)
#> # A tibble: 3 × 4
#> sig adf sadf gsadf
#> <fct> <dbl> <dbl> <dbl>
#> 1 90 0.926 2.43 3.48
#> 2 95 1.32 2.79 3.91
#> 3 99 2.05 3.30 4.93
# }