R: Models for Survival Analysis

# Models for Survival Analysis

## Documentation for package ‘survivalmodels’ version 0.1.13

- DESCRIPTION file.

## Help Pages

survivalmodels-package | survivalmodels: Models for Survival Analysis
akritas | Akritas Conditional Non-Parametric Survival Estimator
build_keras_net | Build a Keras Multilayer Perceptron
build_pytorch_net | Build a Pytorch Multilayer Perceptron
cindex | Compute Concordance of survivalmodel Risk
coxtime | Cox-Time Survival Neural Network
deephit | DeepHit Survival Neural Network
deepsurv | DeepSurv Survival Neural Network
dnnsurv | DNNSurv Neural Network for Conditional Survival Probabilities
get_keras_optimizer | Get Keras Optimizer
get_pycox_activation | Get Pytorch Activation Function
get_pycox_callbacks | Get Torchtuples Callbacks
get_pycox_init | Get Pytorch Weight Initialization Method
get_pycox_optim | Get Pytorch Optimizer
install_keras | Install Keras and Tensorflow
install_pycox | Install Pycox With Reticulate
install_torch | Install Torch With Reticulate
loghaz | Logistic-Hazard Survival Neural Network
pchazard | PC-Hazard Survival Neural Network
predict.akritas | Predict method for Akritas Estimator
predict.dnnsurv | Predict Method for DNNSurv
predict.pycox | Predict Method for pycox Neural Networks
pycox_prepare_train_data | Prepare Data for Pycox Model Training
requireNamespaces | Vectorised Logical requireNamespace
set_seed | Set seed in R numpy and torch
simsurvdata | Simulate Survival Data
survivalmodels | survivalmodels: Models for Survival Analysis
surv_to_risk | Safely convert a survival matrix prediction to a relative risk