Runs Monte Carlo simulation to investigate the optimal number of points to use when one of the reduced spacing schemes is considered.
ComputeBest_tau(AlphaBetaMatrix = abMat, nb_ts = seq(10, 100, 10),
tScheme = c("uniformOpt", "ArithOpt"),
Constrained = TRUE, alphaReg = 0.001, ...)a list containing slots from class Best_t-class
corresponding to one value of the parameters \(\alpha\) and
\(\beta\).
values of the parameter \(\alpha\) and \(\beta\) from which we simulate the data. By default, the values of \(\gamma\) and \(\delta\) are set to 1 and 0, respectively; a \(2 \times n\) matrix.
vector of number of t-points to use for the minimisation;
default = seq(10,100,10).
scheme used to select the points where the moment conditions are
evaluated, one of "uniformOpt" (uniform optimal placement)
and "ArithOpt" (arithmetic optimal placement). See function
GMMParametersEstim.
logical flag: if set to True, lower and upper bands will be computed
as discussed for function GMMParametersEstim.
value of the regularisation parameter; numeric, default = 0.001.
Other arguments to pass to the optimisation function.
ComputeBest_t,
Best_t-class