Set control parameters for nlrq
Set algorithmic parameters for nlrq (nonlinear quantile regression function)
nlrq.control(maxiter=100, k=2, InitialStepSize = 1, big=1e+20, eps=1e-07, beta=0.97)
maximum number of allowed iterations
the number of iterations of the Meketon algorithm to be calculated in each step, usually 2 is reasonable, occasionally it may be helpful to set k=1
Starting value in
optimto determine the step length of iterations. The default value of 1 is sometimes too optimistic. In such cases, the value 0 forces optim to just barely stick its toe in the water.
a large scalar
tolerance for convergence of the algorithm
a shrinkage parameter which controls the recentering process in the interior point algorithm.