Package: TRES Type: Package Title: Tensor Regression with Envelope Structure Version: 1.1.5 Date: 2021-10-19 Authors@R: c( person("Wenjing", "Wang", email = "wenjing.wang@stat.fsu.edu", role = c("aut")), person("Jing", "Zeng", email = "jing.zeng@stat.fsu.edu", role = c("aut", "cre")), person("Xin", "Zhang", email = "henry@stat.fsu.edu", role = c("aut"))) Description: 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) . For details of TPR, see Zhang X, Li L (2017) . For details of 1D algorithm, see Cook RD, Zhang X (2016) . For details of ECD algorithm, see Cook RD, Zhang X (2018) . For more details of the package, see Zeng J, Wang W, Zhang X (2021) . License: GPL-3 Encoding: UTF-8 Language: en-US LazyData: true Depends: R (>= 3.6.0), ManifoldOptim (>= 1.0.0) Imports: MASS, methods, pracma (>= 2.2.5), rTensor (>= 1.4), stats URL: https://github.com/leozeng15/TRES BugReports: https://github.com/leozeng15/TRES/issues RcppModules: ManifoldOptim_module RoxygenNote: 7.1.2 NeedsCompilation: no Suggests: testthat (>= 2.1.0) Repository: https://jingzzeng.r-universe.dev Date/Publication: 2021-11-12 00:30:57 UTC RemoteUrl: https://github.com/jingzzeng/tres RemoteRef: HEAD RemoteSha: 8e1def6faba478821588a74b09d9baa55a043bdf Packaged: 2026-10-03 09:36:17 UTC; root Author: Wenjing Wang [aut], Jing Zeng [aut, cre], Xin Zhang [aut] Maintainer: Jing Zeng