predict_best_lambda: Predict from the optimal lambda from tfCox_choose_lambda
In tfCox: Fits Piecewise Polynomial with Data-Adaptive Knots in Cox Model

Description Usage Arguments Value Author(s) References See Also Examples

Estimate the corresponding theta values from the optimal tuning parameter obtained by tfCox_choose_lambda.

1	predict_best_lambda(cv, newX)

`cv`	An object from tfCox_choose_lambda.
`newX`	The new covariate values.

Estimated theta values.

Jiacheng Wu

Jiacheng Wu & Daniela Witten (2019) Flexible and Interpretable Models for Survival Data, Journal of Computational and Graphical Statistics, DOI: 10.1080/10618600.2019.1592758

tfCox_choose_lambda, negloglik

#generate training and testing data
dat = sim_dat(n=100, zerof=0, scenario=1)
test_dat = sim_dat(n=100, zerof=0, scenario=1)

#choose the optimal tuning parameter
cv = tfCox_choose_lambda(dat, test_dat, ord=0, alpha=1)
plot(cv$lam_seq, cv$loss)

#optimal tuning parameter
cv$best_lambda

#Estimate the theta values of testing covariates from the optimal tuning parameter
#from tfCox_choose_lambda object. 
theta_hat = predict_best_lambda(cv, test_dat$X)