Description Usage Arguments Value Author(s) Examples
Generate simulation data for benchmarking sparse logistic regression models.
1 2 | msaenet.sim.binomial(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>
1 2 3 4 5 6 7 8 9 10 |
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