Description Usage Arguments Author(s) References See Also Examples
Calculate the negative log likelihood from Cox model from the estimated coefficient matrix theta.
1 | negloglik(dat, theta)
|
dat |
A list that contains |
theta |
An n x p matrix of coefficients corresponding to covariates |
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
predict_best_lambda
, tfCox_choose_lambda
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | #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$best_lambda
#predict the coefficients of testing covariates from the optimal tuning parameter
#from tfCox_choose_lambda object.
theta_hat = predict_best_lambda(cv, test_dat$X)
#calculate the loss in the testing data based on the estimated coefficients theta
negloglik(test_dat, theta_hat)
|
[1] 0.02995218
[1] 3.166083
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