Tenv-deprecated

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

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

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 (TRR).

internal

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. For details of TRR, see Li L, Zhang X (2017) <doi:10.1080/01621459.2016.1193022>. For details of TPR, see Zhang X, Li L (2017) <doi:10.1080/00401706.2016.1272495>. For details of 1D algorithm, see Cook RD, Zhang X (2016) <doi:10.1080/10618600.2015.1029577>. For details of ECD algorithm, see Cook RD, Zhang X (2018) <doi:10.5705/ss.202016.0037>.

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Tenv-deprecated: Tensor response envelope estimator

Description

Usage

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References

See Also