coef.cv.hdqr {hdqr} | R Documentation |
Extract Coefficients from a 'cv.hdqr' Object
Description
Retrieves coefficients from a cross-validated 'hdqr()' model, using the stored '"hdqr.fit"' object and the optimal 'lambda' value determined during cross-validation.
Usage
## S3 method for class 'cv.hdqr'
coef(object, s = c("lambda.1se", "lambda.min"), ...)
Arguments
object |
A fitted 'cv.hdqr()' object from which coefficients are to be extracted. |
s |
Specifies the value(s) of the penalty parameter 'lambda' for which coefficients are desired. The default is 's = "lambda.1se"', which corresponds to the largest value of 'lambda' such that the cross-validation error estimate is within one standard error of the minimum. Alternatively, 's = "lambda.min"' can be used, corresponding to the minimum of the cross-validation error estimate. If 's' is numeric, these are taken as the actual values of 'lambda' to use. |
... |
Not used. |
Value
Returns the coefficients at the specified 'lambda' values.
See Also
Examples
set.seed(315)
n <- 100
p <- 400
x <- matrix(data = rnorm(n * p, mean = 0, sd = 1), nrow = n, ncol = p)
beta_star <- c(c(2, 1.5, 0.8, 1, 1.75, 0.75, 0.3), rep(0, (p - 7)))
eps <- rnorm(n, mean = 0, sd = 1)
y <- x %*% beta_star + eps
tau <- 0.5
lam2 <- 0.01
cv.fit <- cv.hdqr(x = x, y = y, tau = tau, lam2 = lam2)
coef(cv.fit, s = c(0.02, 0.03))