Extract coefficients from a psvr_rmspe model

Usage

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

Arguments

object: An object of class "psvr_rmspe".
...: Ignored.

Value

A named list with components:

alpha: Dual variables / Lagrange multipliers (length N).
b: Bias term.
support_data: Training input matrix (all N observations).

Three components, against five for the MAPE classes (coef.psvr_mape()): LS-SVR has no alpha_star and no pruned beta, and they are not materialised as NULL. So names(coef(fit)) depends on the model family, which is a decision rather than an oversight – each class is family-specific, and inventing empty slots to make the two agree would add structure with nothing to inherit it from. $alpha_star and $beta yield NULL on both, so every accessor still agrees.

Renamed in 0.0.2.9011

support_data was named X_sv. LS-SVR performs no pruning — every training point contributes to f(x) — so there are no support vectors to name: it was an epsilon-SVR name on an LS-SVR value. The value is unchanged.