survivalmodels
implements models for survival analysis that are either
not already implemented in R, or novel implementations for speed
improvements. Currently implemented are five neural networks from the
Python packages pycox, DNNSurv, and
the Akritas non-parametric conditional estimator. Further updates will
include implementations of novel survival models.
survivalmodels
implements models from Python using
reticulate. In order to
use these models, the required Python packages must be installed
following with
reticulate::py_install.
survivalmodels
includes a helper function to install the required
pycox
function (with pytorch if also required). Before running any
models in this package, if you have not already installed pycox
please
run
install_pycox(method = "auto", conda = "auto", pip = FALSE, install_torch = FALSE)
With the arguments changed as you require, see ?install_pycox for more.
For DNNSurv
the model depends on keras
and tensorflow
, which
require installation via:
install_keras(method = "auto", conda = "auto", pip = FALSE, install_tensorflow = FALSE)
Install the latest release from CRAN:
install.packages("survivalmodels")
Install the development version from GitHub:
remotes::install_github("RaphaelS1/survivalmodels")