[R] applying summary() to an object created with ols()

[Benjamin Volland]

Hello R-list,

I am trying to calculate a ridge regression using first the *lm.ridge()* 
function from the MASS package and then applying the obtained Hoerl 
Kennard Baldwin (HKB) estimator as a penalty scalar to the *ols()* 
function provided by Frank Harrell 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      38.59      8.814     0.9839    0.02796
 >
 >Residuals:
 >        1         2         3         4         5         6         
7         8         9        10
 >-0.014653 -0.002787  0.017515 -0.018145 -0.008757 -0.008035  0.006066  
0.045826 -0.001244 -0.015786
 >
 >Coefficients:
 >            Value Std. Error       t Pr(>|t|)
 >Intercept  1.5240     3.3034  0.4613   0.8496
 >lntex      0.3722     0.2071  1.7975   0.6801
 >lnbeerp    0.9085     0.5760  1.5771   0.6964
 >lnwinep   -0.1458     0.1874 -0.7781   0.7863
 >lntemp    -0.0772     0.1344 -0.5743   0.8240
 >pop       -4.1889     1.9286 -2.1720   0.6571
 >
 >Adjusted R-Squared: 0.2227

All in all beautiful (leaving aside that the results suck). The problem 
starts when I want to write the obtained coefficients (incl. Std. 
Errors, t-, and p-values) into a matrix.
Via the *f$coef* command I can only access the betas (1st column) and 
using the *summary(f)* function I get
 > summary(f)
 >Fehler in summary.Design(f) :
 >adjustment values not defined here or with datadist for lntex lnbeerp 
lnwinep lntemp pop

Does anyone know how I can set the *datadist()* and the *options()* such 
that I will get access to all coefficients?

I tried:
 > options(datadist=NULL)
 > f <- ols(lnbcpc ~ lntex + lnbeerp + lnwinep + lntemp + pop, 
subset(aa, Jahr>=1957 & Jahr<=1966), penalty = rrk$kHKB)
 > d <- datadist(f)
but got:
 > Fehler in sort.list(unique(y)) : 'x' must be atomic for 'sort.list'
 > Have you called 'sort' on a list?

In the R documentation on ?ols() it states concerning the values 
returned: "the same objects returned from |lm| (/unless |penalty| or 
|penalty.matrix| are given/ - then an abbreviated list is returned since 
|lm.pfit| is used as a fitter)..." Unfortunately no information seems to 
be available on lm.pfit.
Does anyone know why the using that function leads to an abbreviated 
return list? Is there a trick to circumvent that?

Thanks
Benjamin Volland

P.S. Currently using R-version 2.7.1 on a Windows PC.