Estimate Survival Data with Data Integration

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Documentation for package ‘survkl’ version 1.0.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

cal_surv_prob	Calculate Survival Probabilities
coef.coxkl	Extract Coefficients from a 'coxkl' Object
coef.coxkl_enet	Extract Coefficients from a 'coxkl_enet' Object
coef.coxkl_ridge	Extract Coefficients from a 'coxkl_ridge' Object
coxkl	Cox Proportional Hazards Model with KL Divergence for Data Integration
coxkl_enet	Cox Proportional Hazards Model with KL Divergence for Data Integration and Lasso & Elastic Net Penalty
coxkl_ridge	Cox Proportional Hazards Model with Ridge Penalty and External Information
cv.coxkl	Cross-Validated Selection of Integration Parameter ('eta') for the Cox–KL Model
cv.coxkl_enet	Cross-Validation for CoxKL Model with elastic net & lasso penalty
cv.coxkl_ridge	Cross-Validation for CoxKL Ridge Model (eta tuning)
cv.plot	Plot Cross-Validation Results vs Eta
ExampleData_highdim	Example high-dimensional survival data
ExampleData_lowdim	Example low-dimensional survival data
generate_eta	Generate a Sequence of Tuning Parameters (eta)
loss_fn	Calculate the Log-Partial Likelihood for a Stratified Cox Model
plot.coxkl	Plot Model Performance vs Eta for 'coxkl'
plot.coxkl_enet	Plot Model Performance vs Lambda for 'coxkl_enet'
plot.coxkl_ridge	Plot Model Performance vs Lambda for 'coxkl_ridge'
predict.coxkl	Predict Linear Predictors from a 'coxkl' Object
predict.coxkl_enet	Predict Linear Predictors from a coxkl_enet Object
predict.coxkl_ridge	Predict Linear Predictors from a coxkl_ridge Object
support	Study to Understand Prognoses Preferences Outcomes and Risks of Treatment
test_eval	Evaluate model performance on test data