print.coxlps

Print method for a <code>coxlps</code> object.

Laplace approximations and penalized B-splines are combined
for fast Bayesian inference in latent Gaussian models. The routines can be
used to fit survival models, especially proportional hazards and promotion
time cure models (Gressani, O. and Lambert, P. (2018)
<doi:10.1016/j.csda.2018.02.007>). The Laplace-P-spline methodology can also
be implemented for inference in (generalized) additive models
(Gressani, O. and Lambert, P. (2021) <doi:10.1016/j.csda.2020.107088>).
See the associated website for more information and examples.

Oswaldo Gressani

blapsr

Bayesian Inference with Laplace Approximations and P-Splines

Philippe Lambert

print.coxlps function

<dl><dt>x</dt>
<dd>An object of class <code>coxlps</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to print.</dd></dl>

Arguments

Oswaldo Gressani <a href="/link/oswaldo_gressani%40hotmail.fr?package=blapsr&version=0.6.1" data-mini-rdoc="blapsr::oswaldo_gressani@hotmail.fr">oswaldo_gressani@hotmail.fr</a>.

Author

Print a coxlps object. — print.coxlps

<dl>

<dt>x</dt>
<dd>An object of class <code>coxlps</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to print.</dd>

</dl>

Oswaldo Gressani <a href='mailto:oswaldo_gressani@hotmail.fr'>oswaldo_gressani@hotmail.fr</a>.

print.coxlps: Print a coxlps object.

Description

Usage

Arguments

Author

Details

See Also