coef.TFRE: Extract coefficients from a 'TFRE' object

In TFRE: A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression

Extract coefficients from a 'TFRE' object

Description

Extract the coefficient vector from a fitted TFRE Lasso, SCAD or MCP model.

Usage

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

Arguments

object	Fitted "TFRE" model object.
s	Regression model to use for coefficient extraction. Should be one of "1st" and "2nd". See more details in "Details".
...	Not used. Other arguments to extract coefficients.

Details

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

Value

The coefficient vector from the fitted TFRE model, with the first element as the intercept.

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, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/01621459.2020.1840989")}.

See Also

TFRE, predict.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)


Obj_TFRE_Lasso <- TFRE(X, y, second_stage = "none", const_incomplete = 5)
coef(Obj_TFRE_Lasso, "1st")[1:10]
coef(Obj_TFRE_Lasso, "2nd")[1:10]

Obj_TFRE_SCAD <- TFRE(X, y, eta_list = eta_list, const_incomplete = 5)
coef(Obj_TFRE_SCAD, "1st")[1:10]
coef(Obj_TFRE_SCAD, "2nd")[1:10]


Obj_TFRE_MCP <- TFRE(X, y, second_stage = "mcp", eta_list = eta_list, const_incomplete = 5)
coef(Obj_TFRE_MCP, "1st")[1:10]
coef(Obj_TFRE_MCP, "2nd")[1:10]

TFRE documentation built on May 29, 2024, 2:19 a.m.