search for: khkb

...ll in his Design package. It looks like this: > rrk1<-lm.ridge(lnbcpc ~ lntex + lnbeerp + lnwinep + lntemp + pop, subset(aa, Jahr>=1957 & Jahr<=1966)) > f <- ols(lnbcpc ~ lntex + lnbeerp + lnwinep + lntemp + pop, subset(aa, Jahr>=1957 & Jahr<=1966), penalty = rrk$kHKB) > f which returns >Linear Regression Model > >ols(formula = lnbcpc ~ lntex + lnbeerp + lnwinep + lntemp + pop, > data = subset(aa, Jahr >= 1957 & Jahr <= 1966), penalty = rrk$kHKB) > > n Model L.R. d.f. R2 Sigma > 10...

...-longley$Employed 2) X<-as.matrix(cbind(1,Longley[,1:6]) 3) I = identity matrix the following should be true: Coef=(X'X+kI)^(-1) X'y and if a take k=Ridge$kHKV, Coef should be approx equal to Ridge$Coef[near value of kHKV] and it does not seem to happen, why? Values: > Ridge$kHKB [1] 0.004275357 Using the calculation above (third question, third point): Coef= [,1] 1 -0.095492310 GNP.deflator -0.052759002 GNP 0.070993540 Unemployed -0.004244391 Armed.Forces -0.005725582 Population -0.413341544 Year 0.0484...

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