predict.msaenet: Make Predictions from an msaenet Model

In road2stat/msaenet: Multi-Step Adaptive Estimation Methods for Sparse Regressions

Make Predictions from an msaenet Model

Description

Make predictions on new data by a msaenet model object.

Usage

## S3 method for class 'msaenet'
predict(object, newx, ...)

Arguments

object	An object of class msaenet produced by aenet, amnet, asnet, msaenet, msamnet, or msasnet.
newx	New data to predict with.
...	Additional parameters, particularly prediction type in predict.glmnet, predict.ncvreg, or predict.ncvsurv.

Value

Numeric matrix of the predicted values.

Author(s)

Nan Xiao <https://nanx.me>

Examples

dat <- msaenet.sim.gaussian(
  n = 150, p = 500, rho = 0.6,
  coef = rep(1, 5), snr = 2, p.train = 0.7,
  seed = 1001
)

msaenet.fit <- msaenet(
  dat$x.tr, dat$y.tr,
  alphas = seq(0.2, 0.8, 0.2),
  nsteps = 3L, seed = 1003
)

msaenet.pred <- predict(msaenet.fit, dat$x.te)
msaenet.rmse(dat$y.te, msaenet.pred)

road2stat/msaenet documentation built on March 4, 2024, 10:12 p.m.