Robust location estimate with simultaneous estimation of the scale parameter
lywalg(y, lambda, psp0 = psp(0), expsi = psi, exchi = chi, exrho = rho,
sigmai, tol = .dFvGet()$tlo, gam = .dFvGet()$gma,
isigma = .dFvGet()$isg, maxit = .dFvGet()$mxt, maxis = .dFvGet()$mxs,
nitmon = .dFvGet()$ntm)
Final value of the location estimate
Reached number of cycles
Final estimate of sigma
The residual vector
Vector containing the observations
Initial solution of the location parameter
Value of psp(0) (first derivative of the psi function)
User supplied psi function
User supplied chi function
User supplied rho function
Initial estimate of the scale parameter
Relative precision for the convergence criterion
Relaxation factor. Set 0 < gam < 2.
If isigma<0, the value of sigma is not changed during the first iteration. If isigma=0, bypasss iteration on sigma (sigmaf=sigmai). If |isigma|>0, sigma is updated using the robeth function rysigm.
Maximum number of cycles
Maximum number of iterations for the scale step
If nitmon>0 and the iteration counter is a multiple of nitmon, the current value of sigma, theta and delta are printed. If no iteration monitoring is required, set nitmon equal to 0.
The .dFv variables for the default values must be created by a call to the
dfvals() function of the robeth package. To see if this variable is
available in your R session, type ls(all.names=TRUE). The parameters for psi,
chi and rho functions must also be set by a preliminary call to the dfcomn
function of the robeth package.
Marazzi A. (1993), Algorithm, Routines, and S functions for Robust Statistics, Wadsworth & Brooks/cole, Pacific Grove, California. p.30 and p.83 .