This functions is used by numerical optimization algorithms for find maximum p-value given parameter vector theta.
DLMMCpval_fun(
theta,
y,
x,
params,
sim_stats,
pval_type,
stationary_ind,
lambda
)Maximized Monte Carlo p-value.
Value of nuisance parameters. Specifically, these are the consistent estimates of nuisance parameters as discussed in Dufour & Luger (2017) LMC procedure.
series being tested.
lagged values of series.
A (2 x 4) matrix with parameters to combine test statistics. See approxDistDL.
A (N x 1) vector with test statistics. The last element is the test statistic from observed data.
String determining the type of method used to combine p-values. If set to "min" the min method of combining p-values is used as in Fisher 1932 and Pearson 1933. If set to "prod" the product of p-values is used as in Tippett 1931 and Wilkinson 1951.
Boolean indicator determining if only stationary solutions should be considered if TRUE or any solution can be considered if FALSE. Default is TRUE.
Numeric value for penalty on stationary constraint not being met. Default is 100.
Dufour, J. M., & Luger, R. 2017. "Identification-robust moment-based tests for Markov switching in autoregressive models." Econometric Reviews, 36(6-9), 713-727.