>Question 1. Consider the following example from help(ridge):
> fit1 <- coxph(Surv(futime, fustat) ~ rx + ridge(age, ecog.ps, theta=1),
>ovarian)
>As I understand, this builds a model in which `rx' is the predictor,
>whereas ridge penalty term contains variables `age' and
>`ph.ecog'. Could someone explain what it me...
The ridge term introduces age as a predictor AND penalizes it. The model
above has 3 predictors, 2 of them penalized.
Later in the post you have a model with both age and ridge(age). This puts
age in the model twice, once as a free parameter and once as a penalized one.
Not surprisingly, the second ends up with a coefficient of 0 (within machine
precision of zero). The warning message you got about NaN is likely related
to
this, that there are redundant terms in the model.
Terry Therneau
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