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

## 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).

## 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$RMSEP
#> [1] 4.87666
perf$Q2
#> [1] 0.6026672
perf$MAE
#> [1] 3.930114
```