predict.TFRE {TFRE}

Make predictions from a 'TFRE' object

Description

Make predictions for new X values from a fitted TFRE Lasso, SCAD or MCP model.

Usage

## S3 method for class 'TFRE'
predict(object, newX, s, ...)

Arguments

object

Fitted "TFRE" model object.

newX

Matrix of new values for X at which predictions are to be made.

s

Regression model to use for prediction. Should be one of "1st" and "2nd". See more details in "Details".

...

Not used. Other arguments to predict.

Details

If object$second_stage = "none", s cannot be "2nd". If object$second_stage = "none" and s = "2nd", the function will return the predictions based on the TFRE Lasso regression. If object$second_stage = "scad" or "mcp", and s = "2nd", the function will return the predictions based on the TFRE SCAD or MCP regression with the smallest HBIC.

Value

A vector of predictions for the new X values given the fitted TFRE model.

Author(s)

Yunan Wu and Lan Wang
Maintainer: Yunan Wu <[e-mail]>

References

Wang, L., Peng, B., Bradic, J., Li, R. and Wu, Y. (2020), A Tuning-free Robust and Efficient Approach to High-dimensional Regression, Journal of the American Statistical Association, 115:532, 1700-1714, doi:10.1080/01621459.2020.1840989.

See Also

TFRE, coef.TFRE, plot.TFRE

Examples

n <- 20; p <- 50
beta0 <- c(1.5,-1.25,1,-0.75,0.5,rep(0,p-5))
eta_list <- 0.1*6:15*sqrt(log(p)/n)
X <- matrix(rnorm(n*p),n)
y <- X %*% beta0 + rt(n,4)
newX <- matrix(rnorm(10*p),10)


Obj_TFRE_Lasso <- TFRE(X, y, second_stage = "none", const_incomplete = 5)
predict(Obj_TFRE_Lasso, newX, "1st")
predict(Obj_TFRE_Lasso, newX, "2nd")

Obj_TFRE_SCAD <- TFRE(X, y, eta_list = eta_list, const_incomplete = 5)
predict(Obj_TFRE_SCAD, newX, "1st")
predict(Obj_TFRE_SCAD, newX, "2nd")


Obj_TFRE_MCP <- TFRE(X, y, second_stage = "mcp", eta_list = eta_list, const_incomplete = 5)
predict(Obj_TFRE_MCP, newX, "1st")
predict(Obj_TFRE_MCP, newX, "2nd")