RKwei

RKwei computes weight function psi(u)/u for Rocke (translated Tukey's) biweight

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Syntax

Description

example

weiRK =RKwei(u, c, M) Plot of wei function.

Examples

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  • Plot of wei function.

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% Find the values of c and M given bdp=0.4 and v=5 for ARP=0.01
x=0:0.01:5;
bdp=0.4;
v=5;
ARP=0.01;
[c,M]=RKbdp(bdp,v,ARP);
weiRK=RKwei(x,c,M);
% weiRK=weiRK/max(weiRK);
plot(x,weiRK,'LineWidth',2)
xlabel('$u$','Interpreter','Latex')
ylabel('$w (u,c,M)$','Interpreter','Latex')
title('$w (u,c,M)$','Interpreter','Latex')
hold('on')
stem(M,1,'LineStyle',':','LineWidth',1)
text(M,0,'M')
stem(M+c,0,'LineStyle',':','LineWidth',1)
text(M+c,0,'M+c')
    Click here for the graphical output of this example (link to Ro.S.A. website).

    Related Examples

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  • Compare Rocke weight functions for 3 different values of bdp.

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x=0:0.01:6;
% Number of variables v is fixed to 5
v=5;
% ARP is fixed to 0.01
ARP=0.01;
lwd=2;
hold('on')
% Use bdp=0.3
bdp=0.3;
[c,M]=RKbdp(bdp,v,ARP);
weiRK030=RKwei(x,c,M);
weiRK030=weiRK030/max(weiRK030);
plot(x,weiRK030,'LineStyle','-','LineWidth',lwd)
% Use bdp=0.4
bdp=0.4;
[c,M]=RKbdp(bdp,v,ARP);
weiRK040=RKwei(x,c,M);
weiRK040=weiRK040/max(weiRK040);
plot(x,weiRK040,'LineStyle','-.','LineWidth',lwd)
% Use bdp=0.5
bdp=0.5;
[c,M]=RKbdp(bdp,v,ARP);
weiRK050=RKwei(x,c,M);
weiRK050=weiRK050/max(weiRK050);
plot(x,weiRK050,'LineStyle','--','LineWidth',lwd)
xlabel('$x$','Interpreter','Latex','FontSize',16)
ylabel('RK. Normalized $w(x,c,M)$','Interpreter','Latex','FontSize',20)
legend({'$bdp=0.3$', '$bdp=0.4$' '$bdp=0.5$'},'Interpreter','Latex','Location','SouthEast','FontSize',16)
    Click here for the graphical output of this example (link to Ro.S.A. website)

    Input Arguments

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    u — scaled residuals or Mahalanobis distances. Vector.

    n x 1 vector containing residuals or Mahalanobis distances for the n units of the sample

    Data Types: single| double

    c — tuning parameter. Scalar.

    Non negative scalar which (together with the other optional parameter M) controls the robustness/efficiency of the estimator (beta in regression or mu in the location case ...).

    Data Types: single| double

    M — tuning parameter. Scalar.

    Scalar greater than 0 which (together with the other optional parameter c) controls the robustness/efficiency of the estimator (beta in regression or mu in the location case ...).

    Data Types: single| double

    Output Arguments

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    weiRK —Rocke weights (translated Tukey's biweight) associated to the residuals or Mahalanobis distances for the n units of the sample. n -by- 1 vector

    More About

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    Additional Details

    function RKwei transforms vector u as follows \[ RKwei(u)= \left\{ \begin{array}{cc} 1 & 0\leq u \leq M \\ \left(1-\left( \frac{u-M}{c} \right)^2 \right)^2 & M < u \leq M+c \\ 0 & u > M+c \\ \end{array} \right. \]

    See equation (2.18) p. 1332 of Rocke (1996).

    References

    Maronna, R.A., Martin D. and Yohai V.J. (2006), "Robust Statistics, Theory and Methods", Wiley, New York.

    Rocke D.M. (1996), Robustness properties of S-estimators of multivariate location and shape in high dimension, "The Annals of Statistics", Vol. 24, pp. 1327-1345.

    See Also

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