coef.nckqr: Extract model coefficients from a 'nckqr' object.

In fastkqr: A Fast Algorithm for Kernel Quantile Regression

Extract model coefficients from a 'nckqr' object.

Description

Computes the coefficients at the requested value(s) for 'lambda1' for a given 'lambda2' from a [nckqr()] object.

Usage

## S3 method for class 'nckqr'
coef(object, s1 = NULL, s2, ...)

Arguments

object	A fitted nckqr object.
s1	Value(s) of the penalty parameter 'lambda1' at which coefficients are required. Default is the entire sequence used to create the model.
s2	Value of the penalty parameter 'lambda2' at which coefficients are required.
...	Not used.

Details

's1' is the new vector of 'lambda1' values at which predictions are requested. If 's1' is not in the lambda sequence used for fitting the model, the 'coef' function will use linear interpolation to make predictions. The new values are interpolated using a fraction of coefficients from both left and right 'lambda' indices.

Value

The coefficients for the non-crossing kernel quantile regression model.

See Also

[nckqr()] and [predict.nckqr()].

Examples

library(MASS)
data(GAGurine)
x <- as.matrix(GAGurine$Age)
y <- GAGurine$GAG
l2 <- 1e-4
ttau <- c(0.1, 0.3, 0.5, 0.7, 0.9)
l1_list <- 10^seq(-8, 2, length.out=10)
fit <- nckqr(x,y, lambda1=l1_list, lambda2=l2, tau=ttau)
coef(fit, s1=l1_list[1:3], s2=1e-4)

fastkqr documentation built on June 22, 2024, 7 p.m.