Function reference • OHPL

Fit OHPL models

Functions for fitting OHPL models.

OHPL(): Ordered Homogeneity Pursuit Lasso

FOP(): Fisher Optimal Partition

proto(): Extract the Prototype from Each Variable Group

dlc(): Compute D, L, and C in the Fisher Optimal Partitions Algorithm

OHPL-package: Ordered Homogeneity Pursuit Lasso for Group Variable Selection

Evaluate OHPL models

Functions for cross-validation, prediction, performance evaluation, and generation of simulated data.

cv.OHPL(): Cross-Validation for Ordered Homogeneity Pursuit Lasso

predict(<OHPL>): Make Predictions Based on the Fitted OHPL Model

OHPL.RMSEP(): Compute RMSEP, MAE, and Q2 for a Test Set

OHPL.sim(): Generate Simulation Data for Benchmarking Sparse Regressions (Gaussian Response)

Datasets

Real-world spectroscopic datasets used in the paper.

beer: The beer dataset

wheat: The wheat dataset

soil: The soil dataset