Other packages > Find by keyword >

TensorPreAve  

Rank and Factor Loadings Estimation in Time Series Tensor Factor Models
View on CRAN: Click here


Download and install TensorPreAve package within the R console
Install from CRAN:
install.packages("TensorPreAve")

Install from Github:
library("remotes")
install_github("cran/TensorPreAve")

Install by package version:
library("remotes")
install_version("TensorPreAve", "1.1.0")



Attach the package and use:
library("TensorPreAve")
Maintained by
Weilin Chen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-11-08
Latest Update: 2023-04-14
Description:
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) <doi:10.48550/arXiv.2208.04012> for more details.
How to cite:
Weilin Chen (2022). TensorPreAve: Rank and Factor Loadings Estimation in Time Series Tensor Factor Models. R package version 1.1.0, https://cran.r-project.org/web/packages/TensorPreAve. Accessed 07 Mar. 2026.
Previous versions and publish date:
0.1.1 (2022-11-08 15:20)
Other packages that cited TensorPreAve R package
View TensorPreAve citation profile
Other R packages that TensorPreAve depends, imports, suggests or enhances
Complete documentation for TensorPreAve
Functions, R codes and Examples using the TensorPreAve R package
Some associated functions: bs_cor_rank . equal_weight_tensor . iter_proj . pre_est . rank_factors_est . tensor_data_gen . value_weight_tensor . 
Some associated R codes: bs_cor_rank.R . data.R . iter_proj.R . pre_est.R . rank_factors_est.R . tensor_data_gen.R .  Full TensorPreAve package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

SAMtool  
Stock Assessment Methods Toolkit
Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
testDriveR  
Teaching Data for Statistics and Data Science
Provides data sets for teaching statistics and data science courses. It includes a sample of data f ...
Download / Learn more Package Citations See dependency  
ReviewR  
A Light-Weight, Portable Tool for Reviewing Individual Patient Records
A portable Shiny tool to explore patient-level electronic health record data and perform chart revi ...
Download / Learn more Package Citations See dependency  
lmSubsets  
Exact Variable-Subset Selection in Linear Regression
Exact and approximation algorithms for variable-subset selection in ordinary linear regression mode ...
Download / Learn more Package Citations See dependency  
portalr  
Create Useful Summaries of the Portal Data
Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Projec ...
Download / Learn more Package Citations See dependency  

26,264

R Packages

223,360

Dependencies

70,376

Author Associations

26,265

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA