Depends: R (>= 3.6.0), ManifoldOptim (>= 1.0.0)
Imports: MASS, methods, pracma (>= 2.2.5), rTensor (>= 1.4), stats

Title: Tensor Regression with Envelope Structure

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) <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>.

Description: Performs data assimilation, processing and analyses on sap flow data obtained
with the thermal dissipation method (TDM). The package includes functions for gap filling
time-series data, detecting outliers, calculating data-processing uncertainties and
generating uniform data output and visualisation. The package is designed to deal with
large quantities of data and to apply commonly used data-processing methods. The functions
have been validated on data collected from different tree species across
the northern hemisphere (Peters et al. 2018 <doi:10.1111/nph.15241>).
Imports: chron, zoo, solaR, stats, graphics, lubridate, utils,
grDevices, lhs, doParallel, foreach, tibble, dplyr,
sensitivity, randtoolbox, boot, doSNOW, msm, parallel,
Alexander Hurley [aut, cph] (<https://orcid.org/0000-0002-9641-2805>),