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README.md
In lnmixsurv: Bayesian Mixture Log-Normal Survival Model
lnmixsurv
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.
Dependencies
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).
Mac OS
Run brew install gsl at the console/terminal should be enough for
installing GSL.
Linux
The installation of GSL on Linux is distro-specific. For the main
distros out-there:
- Arch:
sudo pacman -S gsl
- CentOS/RHEL:
sudo yum install gsl-devel or
sudo dnf install gsl-devel (make sure the EPEL – Extra Packages for
Enterprise Linux – repository is enabled)
- Debian/Ubuntu:
sudo apt-get install libgsl-dev
- Fedora:
sudo dnf install gsl-devel
- Gentoo:
sudo emerge sci-libs/gsl
- openSUSE:
sudo zypper install gsl-devel
Installation
You 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")
parsnip and censored extension
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 | ✖ | ✔ | ✖ | ✖ | ✖ | ✔ |
Try the lnmixsurv package in your browser
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lnmixsurv documentation built on Sept. 11, 2024, 7:18 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
lnmixsurv
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.
Dependencies
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).
Mac OS
Run brew install gsl at the console/terminal should be enough for
installing GSL.
Linux
The installation of GSL on Linux is distro-specific. For the main distros out-there:
- Arch:
sudo pacman -S gsl - CentOS/RHEL:
sudo yum install gsl-develorsudo dnf install gsl-devel(make sure the EPEL – Extra Packages for Enterprise Linux – repository is enabled) - Debian/Ubuntu:
sudo apt-get install libgsl-dev - Fedora:
sudo dnf install gsl-devel - Gentoo:
sudo emerge sci-libs/gsl - openSUSE:
sudo zypper install gsl-devel
Installation
You 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")
parsnip and censored extension
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 | ✖ | ✔ | ✖ | ✖ | ✖ | ✔ |
Try the lnmixsurv package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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