Extract coefficients

Extracts coefficients from an object of class "cv.corila".

Usage

# S3 method for class 'cv.corila'
coef(object, s = "lambda.min", ...)

Arguments

object: object of class "cv.corila"
s: character "lambda.min" or numeric non-negative scalar
...: (for compatibility with stats::coef)

Value

Returns an \((1 + p)\)-dimensional vector of the estimated coefficients. The first entry is the estimated intercept, and the other \(p\) entries are the estimated slopes.

Details

This function calls .combine_slopes() to combine positive and negative coefficients and .backscale() to bring coefficients back to the original scale.

References

Armin Rauschenberger (2026). "Sparse modelling with grouped and correlated features allowing for privileged information". In preparation.

Examples

# \donttest{
data <- simulate_data()
model <- cv.corila(x = data$x_train,
                   y = data$y_train,
                   group = data$group,
                   primary = data$primary)
#>   wgt_local exp_local wgt_global exp_global threshold      cvm
#> 2       0.1         0        0.9          2         0 10.40527
beta_hat <- coef(object = model)
y_hat <- predict(object = model, newx = data$x_test)
# }

# example for automatic mutation testing (with the R package autotest)
data <- simulate_data()
model <- cv.corila(x = data$x_train,
                   y = data$y_train,
                   group = as.double(data$group),
                   primary = data$primary,
                   alpha_init = 0.0,
                   foldid = rep(x = seq_len(10L),
                                length.out = nrow(data$x_train)))
#>    wgt_local exp_local wgt_global exp_global threshold      cvm
#> 11         1         0          0        Inf         0 10.19317