theta
/2 time the sum of squared coefficients. If scale=T
the penalty is calculated for coefficients based on rescaling the
predictors to have unit variance. If df
is specified then theta
is chosen based on an approximate degrees of freedom.ridge(..., theta, df=nvar/2, eps=0.1, scale=TRUE)
theta
/2 time sum of squared coefficientsdf
coxph.penalty
containing the data and
control functions.coxph
,survreg
,pspline
,frailty
coxph(Surv(futime, fustat) ~ rx + ridge(age, ecog.ps, theta=1),
ovarian)
lfit0 <- survreg(Surv(time, status) ~1, cancer)
lfit1 <- survreg(Surv(time, status) ~ age + ridge(ph.ecog, theta=5), cancer)
lfit2 <- survreg(Surv(time, status) ~ sex + ridge(age, ph.ecog, theta=1), cancer)
lfit3 <- survreg(Surv(time, status) ~ sex + age + ph.ecog, cancer)
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