Package: TensorPreAve 1.1.0

Weilin Chen

TensorPreAve: Rank and Factor Loadings Estimation in Time Series Tensor Factor Models

A set of functions to estimate rank and factor loadings of time series tensor factor models. A tensor is a multidimensional array. To analyze high-dimensional tensor time series, factor model is a major dimension reduction tool. 'TensorPreAve' provides functions to estimate the rank of core tensors and factor loading spaces of tensor time series. More specifically, a pre-averaging method that accumulates information from tensor fibres is used to estimate the factor loading spaces. The estimated directions corresponding to the strongest factors are then used for projecting the data for a potentially improved re-estimation of the factor loading spaces themselves. A new rank estimation method is also implemented to utilizes correlation information from the projected data. See Chen and Lam (2023) <arxiv:2208.04012> for more details.

Authors:Weilin Chen [aut, cre]

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TensorPreAve/json (API)

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

Peer review:

Bug tracker:https://github.com/william-chenwl/tensorpreave/issues

Datasets:

On CRAN:

3.00 score 1 stars 2 scripts 271 downloads 6 exports 3 dependencies

Last updated 2 years agofrom:205bbbf7f7. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-winOKNov 22 2024
R-4.5-linuxOKNov 22 2024
R-4.4-winOKNov 22 2024
R-4.4-macOKNov 22 2024
R-4.3-winOKNov 22 2024
R-4.3-macOKNov 22 2024

Exports:bs_cor_rankiter_projpre_eigenplotpre_estrank_factors_esttensor_data_gen

Dependencies:MASSpracmarTensor

A short introduction to TensorPreAve

Rendered frommy-vignette.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2023-04-16
Started: 2022-11-03