# ComputeBest_tau: Runs Monte Carlo Simulation to investigate the optimal tau. In StableEstim: Estimate the Four Parameters of Stable Laws using Different Methods

## Description

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

## Usage

 1 2 3 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.

ComputeBest_t,Best_t-class