Tenv

The response tensor instance \( r_1\times r_2\times \cdots \times r_m \times n\), where \(n\) is the sample size.

The predictor matrix of dimension \(p \times n\).

The dimension of envelope subspace. \(u=(u_1,\cdots,u_m)\).

The option structure for Feasi. See function <code>OptimballGBB1D</code>.

opts

This function gives the tensor envelope estimator for tensor response regression.

Provides three estimators for tensor response regression (TRR) and tensor predictor regression (TPR) models with tensor envelope structure. The three types of estimation approaches are generic and can be applied to any envelope estimation problems. The full Grassmannian (FG) optimization is often associated with likelihood-based estimation but requires heavy computation and good initialization; the one-directional optimization approaches (1D and ECD algorithms) are faster, stable and does not require carefully chosen initial values; the SIMPLS-type is motivated by the partial least squares regression and is computationally the least expensive.

Tenv: Tensor response envelope estimator

Description

Usage

Arguments

Value

References