This class of objects is returned by the coxph_mpl class of functions
to represent a proportional hazards model fitted by maximum penalised likelihood.
Objects of this class have methods for the functions print,
summary, plot, residuals and predict.
All components described under Arguments must be included in a legitimate
coxph_mpl object.
a list of length 2 containg the parameter estimates of each model part.
The first list, named 'Beta', contains the vector of regression parameter
estimates of length \(p\). The second list, named 'Theta', contains the
vector of the baseline hazard parameter estimates of length \(m\).
a list of length 2 containg the parameter standard errors of each model part.
The first list, named 'Beta', is a (\(p\) x \(5\)) matrix indicating
the standard errors of each regression parameter according to 5 inference methods.
See Details in coxph_mpl. The second list, named 'Theta',
is a (\(m\) x \(5\)) matrix indicating the standard errors of each baseline
hazard parameter according to 5 inference methods. See Details in
coxph_mpl.
a list of length 5 containg the (\(p+m\) x \(p+m\)) covariance matrix according to
5 inference methods. See Details in coxph_mpl.
a vector of length 2. The first element is the penalised log-likelihood with the final values of the coefficients. (The second element is a correction factor for the baseline hazard parameters due to the use of a centered X matrix in the estimation process.)
a vector of length 3 indicating the number of iterations used to estimate the
smoothing parameter (first value, equal to 1 when the user specified a
chosen value), the Beta and Theta parameters during the entire process (second
value), and Beta and Theta parameters during the last smoothing parameter iteration
(third value).
list of length 3 to 4 containg parameters of the chosen basis: 'm', the number
of used bases; 'Alpha', the knot sequence of length \(m+1\) for the uniform
basis, and of length \(m\) otherwise; 'Delta', the value of the integral of
each base over the data support (which equals 1 when basis != 'uniform');
'Sigma', only available for the Gaussian basis, corresponds to the standard
deviation of each truncated Gaussian base.
Object of class coxph_mpl.control specifying the basis, smoothing parameter
value and other options. See coxph_mpl.control.
a list of length 5 with following elements: 'n', the sample size; 'n.events',
the number of events; 'n.ties', the number of duplicated observations; 'p',
the number of regression parameters; and 'm', the number of baseline hazard
parameters.
number of iterations used.
the matched call.
a list of length 3 with following elements: 'time', the outcome vector with
an added noise applied to duplicated observation if ties == "epsilon"
in coxph_mpl.control; 'observed', a logical vector indicating
if outcomes are fully observed or censored; 'X', the X matrix corresponding
to the model formula indicated in coxph_mpl.
coxph_mpl, summary.coxph_mpl, coef.coxph_mpl,
plot.coxph_mpl,residuals.coxph_mpl
and predict.coxph_mpl.