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The lnmixsurv package provides an easy interface to the
Bayesian lognormal mixture model proposed by Lobo,
Fonseca and Alves, 2023.
An usual formula-type model is implemented in
survival_ln_mixture, with the usual
suvival::Surv() interface. The model tries to follow the conventions
for R modeling packages, and uses the hardhat structure.
The underlying algorithm implementation is a Gibbs sampler which
takes initial values from a small run of the EM-Algorithm, with initial
values selection based on the log-likelihood. Besides the Bayesian
approach, the Expectation-Maximization approach (which focus on
maximizing the likelihood) for censored data is also available. The
methods are implemented in C++ using
RcppArmadillo for the linear algebra operations,
RcppGSL for the random number generation and seed control
and RcppParallel (since version 3.0.0) for
parallelization.
The only dependency is on GSL, so, make sure you have GSL installed before proceeding Below, there are some basic guides on how to install these for each operational system other than Windows (Windows users are probably fine and ready to go).
Run brew install gsl at the console/terminal should be
enough for installing GSL.
The installation of GSL on Linux is distro-specific. For the main distros out-there:
sudo pacman -S gslsudo yum install gsl-devel or
sudo dnf install gsl-devel (make sure the EPEL – Extra
Packages for Enterprise Linux – repository is enabled)sudo apt-get install libgsl-devsudo dnf install gsl-develsudo emerge sci-libs/gslsudo zypper install gsl-develYou can install the latest development version of
lnmixsurv from GitHub:
# install.packages("devtools")
devtools::install_github("vivianalobo/lnmixsurv")Alternatively, to install the latest development version of
lnmixsurv, you can use the following code:
# install.packages("devtools")
devtools::install_github("vivianalobo/lnmixsurv", "devel")An extension to the models defined by parsnip and censored
is also provided, adding the survival_ln_mixture engine to
the parsnip::survival_reg() model.
The following models, engines, and prediction type are
available/extended through persistencia:
| model | engine | time | survival | linear_pred | raw | quantile | hazard |
|---|---|---|---|---|---|---|---|
| survival_reg | survival_ln_mixture | ✖ | ✔ | ✖ | ✖ | ✖ | ✔ |
| survival_reg | survival_ln_mixture_em | ✖ | ✔ | ✖ | ✖ | ✖ | ✔ |
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.