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Summary method for experimental multivariate PLS2 CV models

summary.cv.plsRmultiModel.Rd

Summarizes repeated k-fold cross-validation results from cv.plsRmulti.

Usage

# S3 method for class 'cv.plsRmultiModel'
summary(object, verbose = TRUE, ...)

Arguments

object

An object of class "cv.plsRmultiModel".

verbose

Should progress information be displayed?

...

Further arguments passed to methods.

Value

A list of per-partition summary matrices with the same aggregate columns used by summary.cv.plsRmodel for Q2, PRESS, and RSS, plus response-specific PRESS, RSS, Q2, and R2 columns.

Details

The returned object inherits from "summary.cv.plsRmodel" so that cvtable and the existing plot method can be reused for the aggregated multivariate criteria.

See also

cv.plsRmulti, cvtable

Examples

set.seed(123)
X <- matrix(rnorm(60 * 4), ncol = 4)
Y <- cbind(
  y1 = X[, 1] - 0.5 * X[, 2] + rnorm(60, sd = 0.1),
  y2 = 0.3 * X[, 2] + X[, 3] + rnorm(60, sd = 0.1)
)

cv_fit <- cv.plsRmulti(Y, X, nt = 2, K = 3, NK = 1, verbose = FALSE)
summary(cv_fit, verbose = FALSE)
#> [[1]]
#>           AIC     Q2cum_Y LimQ2_Y        Q2_Y   PRESS_Y      RSS_Y      R2_Y
#> Nb_Comp_0  NA          NA      NA          NA        NA 118.000000        NA
#> Nb_Comp_1  NA -0.08370946  0.0975 -0.08370946 59.406927  54.818131 0.5354396
#> Nb_Comp_2  NA -0.76796595  0.0975 -0.63140215  4.509567   2.764228 0.9765743
#>           AIC.std   PRESS_y1     RSS_y1        Q2_y1     R2_y1  PRESS_y2
#> Nb_Comp_0      NA         NA 59.0000000           NA        NA        NA
#> Nb_Comp_1      NA 31.6161004 31.8142050  0.006226923 0.4607762 27.790827
#> Nb_Comp_2      NA  0.7826158  0.5521728 -0.417338684 0.9906411  3.726952
#>              RSS_y2      Q2_y2     R2_y2
#> Nb_Comp_0 59.000000         NA        NA
#> Nb_Comp_1 23.003926 -0.2080906 0.6101030
#> Nb_Comp_2  2.212055 -0.6848366 0.9625075
#> attr(,"computed_nt")
#> [1] 2
#> 
#> attr(,"class")
#> [1] "summary.cv.plsRmultiModel" "summary.cv.plsRmodel"