Monte Carlo Critical Values for Reverse-Regression Recovery Dating

Computes critical values for the reverse-regression BSADF statistic used by radf_recovery, calibrated to its own (Phillips & Shi 2014's Theorem 1) null limiting distribution rather than the standard forward radf_mc_cv boundary – reversing the simulated null path before running the recursive computation, since reversal induces an endogeneity with no forward-regression analogue (see radf_recovery's Details).

Usage

radf_recovery_cv(n, minw = NULL, nrep = 1000L, seed = NULL, lag = 0)

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. Either NULL or an integer will be used in a call to set.seed before simulation. If set, the value is saved as "seed" attribute of the returned value. The default, NULL, will not change rng state, and return .Random.seed as the "seed" attribute. Results are reproducible across the parallel and non-parallel option when the same seed is used.

lag

A non-negative integer. Number of lags in the auxiliary regression, as in radf.

Value

A list of class radf_cv with a single element, bsadf_cv: a matrix of critical values (columns 90%, 95%, 99%), one row per reverse-time position, aligned the same way radf_mc_cv's own bsadf_cv aligns to radf()$bsadf.

Status

See also

radf_recovery, radf_mc_cv

Examples

# \donttest{
cv <- radf_recovery_cv(n = 100, minw = 20, nrep = 200)
print(cv)
#> 
#> ── Monte Carlo (reverse) (minw = 20, nboot = 200) ──────────────────────────────
#> 
#> Error in UseMethod("tidy_radf_cv"): no applicable method for 'tidy_radf_cv' applied to an object of class "c('radf_cv', 'recovery_cv', 'list')"
# }