Description Usage Arguments Value Author(s) References Examples
Generate simulation data for benchmarking sparse Cox regression models.
1 2 | msaenet.sim.cox(n = 300, p = 500, rho = 0.5, coef = rep(0.2, 50),
snr = 1, p.train = 0.7, seed = 1001)
|
n |
Number of observations. |
p |
Number of variables. |
rho |
Correlation base for generating correlated variables. |
coef |
Vector of non-zero coefficients. |
snr |
Signal-to-noise ratio (SNR). |
p.train |
Percentage of training set. |
seed |
Random seed for reproducibility. |
List of x.tr
, x.te
, y.tr
, and y.te
.
Nan Xiao <https://nanx.me>
Simon, N., Friedman, J., Hastie, T., & Tibshirani, R. (2011). Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent. Journal of Statistical Software, 39(5), 1–13.
1 2 3 4 5 6 7 8 9 10 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.