Package: TRES 1.1.5

Jing Zeng

TRES: Tensor Regression with Envelope Structure

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>. For more details of the package, see Zeng J, Wang W, Zhang X (2021) <doi:10.18637/jss.v099.i12>.

Authors:Wenjing Wang [aut], Jing Zeng [aut, cre], Xin Zhang [aut]

TRES_1.1.5.tar.gz
TRES_1.1.5.zip(r-4.5)TRES_1.1.5.zip(r-4.4)TRES_1.1.5.zip(r-4.3)
TRES_1.1.5.tgz(r-4.4-any)TRES_1.1.5.tgz(r-4.3-any)
TRES_1.1.5.tar.gz(r-4.5-noble)TRES_1.1.5.tar.gz(r-4.4-noble)
TRES_1.1.5.tgz(r-4.4-emscripten)TRES_1.1.5.tgz(r-4.3-emscripten)
TRES.pdf |TRES.html✨
TRES/json (API)
NEWS

# Install 'TRES' in R:
install.packages('TRES', repos = c('https://jingzzeng.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/leozeng15/tres/issues

Datasets:
  • EEG - Electroencephalography (EEG) dataset for alcoholism study.
  • bat - Bat simulated data
  • square - Square simulated data

On CRAN:

22 exports 2 stars 2.71 score 6 dependencies 1 dependents 11 mentions 19 scripts 243 downloads

Last updated 3 years agofrom:8e1def6fab. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 03 2024
R-4.5-winOKSep 03 2024
R-4.5-linuxOKSep 03 2024
R-4.4-winOKSep 03 2024
R-4.4-macOKSep 03 2024
R-4.3-winOKSep 03 2024
R-4.3-macOKSep 03 2024

Exports:ECDFGfunkroncovmanifold1DmanifoldFGMenvU_simoneD_bicOptM1DOptMFGOptStiefelGBBPMSEsimplsMUstd_errsubspaceTenv_PvalTPR.fitTPRdimTPRsimTRR.fitTRRdimTRRsimttt

Dependencies:ManifoldOptimMASSpracmaRcppRcppArmadillorTensor

Readme and manuals

Help Manual

Help pageTopics
Tensor Regression with Envelope StructureTRES-package TRES
Bat simulated databat
ECD algorithm for estimating the envelope subspaceECD
Electroencephalography (EEG) dataset for alcoholism study.EEG
The Objective function and its gradientFGfun
The covariance estimation of tensor normal distributionkroncov
Estimate the envelope subspace ('ManifoldOptim' 1D)manifold1D
Estimate the envelope subspace ('ManifoldOptim' FG)manifoldFG
Generate matrices M and UMenvU_sim
Envelope dimension selection based on 1D-BIConeD_bic
Estimate the envelope subspace ('OptM' 1D)OptM1D
Estimate the envelope subspace ('OptM' FG)OptMFG
Optimization on Stiefel manifoldOptStiefelGBB
Plot coefficients and p-value for Tenv object.plot.Tenv
Prediction and mean squared error.PMSE
Predict method for Tenv object.predict.Tenv
SIMPLS-type algorithm for estimating the envelope subspacesimplsMU
Square simulated datasquare
Elementwise standard error.std_err
The distance between two subspaces.subspace
Summarize method for Tenv object.print.summary.Tenv summary.Tenv
The p-value and standard error of coefficient in tensor response regression (TRR) model.Tenv_Pval
Tensor predictor regressionTPR TPR.fit
Envelope dimension by cross-validation for tensor predictor regression (TPR).TPRdim
Generate simulation data for tensor predictor regression (TPR)TPRsim
Tensor response regressionTRR TRR.fit
Envelope dimension selection for tensor response regression (TRR)TRRdim
Generate simulation data for tensor response regression (TRR)TRRsim
Matrix product of two tensorsttt