On 8/23/2011 3:35 AM, Liviu Andronic wrote:
[snip]
But how does one obtain the customary 'lm' summary information for the
model above? I tried supplying the chosen lambda to Design::ols()
using its 'penalty' argument, but strangely the results differ. See
below.
require(Design)
Design::ols(Employed ~ GNP.deflator + GNP + Unemployed + Armed.Forces +
Population + Year,data=longley,penalty = 0.03,tol=1e-12)
First, you should be using rms::ols, as Design is old.
Second, penalty in ols() is not the same as the ridge constant in
lm.ridge, but rather a penalty on the log likelihood. The documentation
for ols refers to ?lrm for the description.
Third, other ridge estimators (e.g., ElemStatLearn::simple.ridge also
give slightly different results for the same data due to differences in
the way scaling is handled.
hth,
-Michael
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
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