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

[Mark Difford]

Hi Benjamin,

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

## Do this before you fit your models, i.e. tell datadist &c what data set
you are using.
d <- datadist( subset(aa, Jahr>=1957 & Jahr<=1966) )
options( datadist = "d" )
d

You can specify the limits yourself when you call plot.Design or
summary.Design, but this automates the process.

Regards, Mark.


Benjamin Volland wrote:
> 
> 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.
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 
> 

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