coxph
and
survReg
.
It fits a smoothing spline using the p-spline basis.
pspline(x, df=4, theta, nterm=2.5 * df, degree=3, eps=0.1, method, ...)
df
or
theta
must be given,
but not both.
If
df=0
,
then the AIC for the term (loglik -df) is used to choose an
"optimal" degrees of freedom.
If AIC is chosen, then an optional argument
caic=T
can be used
to specify the corrected AIC of Hurvich et. al.
theta=1
corresponding to a linear fit
and
theta=0
to an unconstrained fit
of
nterm
degrees of freedom.
theta
.
If
theta
is given,
then
"fixed"
is assumed.
If the degrees of freedom is given,
then
"df"
is assumed.
If
method="aic"
,
then the degrees of freedom is chosen automatically
using Akaike's information criterion.
coxph
or
survReg
functions.
Eilers, Paul H. and Marx, Brian D. (1996). Flexible smoothing with B-splines and penalties. Statistical Science, 11, 89-121.
Hurvich, C. M. and Simonoff, J. S. and Tsai, Chih-Ling (1998). Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion. JRSSB, 60, 271-293.
# No evidence for a non-linear age effect: coxph(Surv(time, status) ~ pspline(age) + sex + strata(inst), data=lung, na.action=na.exclude)