TensPLS_cv2d3d: Envelope dimension by cross-validation

In kusakehan/TEReg: An R package for tensor envelope regression with tensor response and tensor predictor

Description

This function obtain the envelope dimension by cross-validation for tensor regression.

Usage

TensPLS_cv2d3d(X0, Y0, maxdim, nfolds)

Arguments

X0	A predictor tensor instance.
Y0	The response vector.
maxdim	The largest dimension to be considered for selection.
nfolds	Number of folds for cross-validation.

Value

mincv	The minimum sum of squared error.
u	The envelope subspace dimension selected.

References

Zhang, X., & Li, L. (2017). Tensor Envelope Partial Least-Squares Regression. Technometrics, 59(4), 426-436.

kusakehan/TEReg documentation built on May 30, 2019, 7:17 a.m.