OPTpsi computes psi function (derivative of rho function) for optimal weight function
psiOPT=OPTpsi(u,c)
example
psiOPT =OPTpsi(u, c) Plot of psi function (derivative of rho function) for optimal weight function.
psiOPT =OPTpsi(u, c)
psiOPT
u
c
expand all
x=-6:0.01:6;psiOPT=OPTpsi(x,1.2);plot(x,psiOPT)xlabel('x','Interpreter','Latex')ylabel('$\psi (x)$','Interpreter','Latex')
n x 1 vector containing residuals or Mahalanobis distances for the n units of the sample
Data Types: single| double
single| double
Scalar greater than 0 which controls the robustness/efficiency of the estimator (beta in regression or mu in the location case ...)
psi function.
function OPTpsi transforms vector u as follows
Remark: Optimal psi-function is almost linear around u = 0 in accordance with Winsor's principle that all distributions are normal in the middle.
This means that \psi(u)/u is approximately constant over the linear region of \psi, so the points in that region tend to get equal weight.
Maronna, R.A., Martin D. and Yohai V.J. (2006), "Robust Statistics, Theory and Methods", Wiley, New York.
HYPpsi | HApsi | TBpsi | OPTrho | OPTpsider | OPTpsix
HYPpsi
HApsi
TBpsi
OPTrho
OPTpsider
OPTpsix