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

In road2stat/OHPL: Ordered Homogeneity Pursuit Lasso for Group Variable Selection

Compute RMSEP, MAE, and Q2 for a Test Set

Description

This function makes predictions on new data and computes the performance evaluation metrics RMSEP, MAE, and Q2.

Usage

OHPL.RMSEP(object, newx, newy)

Arguments

object	An An object of class OHPL fitted by OHPL.
newx	Predictor matrix of the new data.
newy	Response matrix of the new data (matrix with one column).

Value

A list of the performance metrics.

Examples

# generate simulation data
dat <- OHPL.sim(
  n = 100, p = 100, rho = 0.8,
  coef = rep(1, 10), snr = 3, p.train = 0.5,
  seed = 1010
)

# split training and test set
x <- dat$x.tr
y <- dat$y.tr
x.test <- dat$x.te
y.test <- dat$y.te

# fit the OHPL model
fit <- OHPL(x, y, maxcomp = 3, gamma = 0.5, G = 10, type = "max")

# compute evaluation metric RMSEP, Q2 and MAE for the test set
perf <- OHPL.RMSEP(fit, x.test, y.test)
perf$RMSEP
perf$Q2
perf$MAE

road2stat/OHPL documentation built on Feb. 4, 2023, 6:24 a.m.