Predict latent scores from a PLS fit
Examples
set.seed(123)
X <- matrix(rnorm(40), nrow = 10)
y <- X[, 1] - 0.5 * X[, 2] + rnorm(10, sd = 0.1)
fit <- pls_fit(X, y, ncomp = 2, scores = "r")
pls_predict_scores(fit, X, ncomp = 2)
#> t1 t2
#> [1,] -0.13544977 -0.52708945
#> [2,] -0.17098259 -0.14902942
#> [3,] 0.50972517 0.24632134
#> [4,] 0.08135113 0.04355323
#> [5,] 0.08487733 0.26452562
#> [6,] 0.55636410 -0.25130464
#> [7,] 0.08732598 0.20957085
#> [8,] -0.44910850 0.39409855
#> [9,] -0.26198780 -0.48844206
#> [10,] -0.30211506 0.25779599