ComputeBest_tau: Runs Monte Carlo Simulation to investigate the optimal tau.

Description Usage Arguments Value See Also

View source: R/BestT.R

Description

Runs Monte Carlo Simulation to investigate the optimal number of points to use when one of the reduced spacing scheme is considered.

Usage

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ComputeBest_tau(AlphaBetaMatrix = abMat, nb_ts = seq(10, 100, 10),
                tScheme = c("uniformOpt", "ArithOpt"),
                Constrained = TRUE, alphaReg = 0.001, ...)

Arguments

AlphaBetaMatrix

Values of the parameter α and β from which we simulate the data. By default, The values of γ and δ are set to 1 and 0 respectively; matrix 2 \times n

nb_ts

Vector of number of t-points to use for the minimisation; default seq(10,100,10).

tScheme

Scheme used to select the points where the moment conditions are evaluated. User can choose between "uniformOpt" (uniform optimal placement) and "ArithOpt" (arithmetic optimal placement). See function GMMParametersEstim

Constrained

Logical flag: if set to True lower and upper bands will be computed as discussed function GMMParametersEstim.

alphaReg

Value of the regularisation parameter; numeric, default=0.001.

...

Other arguments to pass to the optimisation function.

Value

Returns a list containing slots from class Best_t-class corresponding to one value of the parameters α and β.

See Also

ComputeBest_t,Best_t-class



StableEstim documentation built on May 19, 2017, 10:37 p.m.
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