CRAN/E | TensorPreAve

TensorPreAve

Rank and Factor Loadings Estimation in Time Series Tensor Factor Models

Installation

About

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) for more details.

github.com/William-Chenwl/TensorPreAve

Key Metrics

Version 1.1.0
R ≥ 2.10
Published 2023-04-14 349 days ago
Needs compilation? no
License GPL-3
CRAN checks TensorPreAve results

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Maintainer

Maintainer

Weilin Chen

w.chen56@lse.ac.uk

Authors

Weilin Chen

aut / cre

Material

Reference manual
Package source

In Views

TimeSeries

Vignettes

A short introduction to TensorPreAve

macOS

r-devel

arm64

r-release

arm64

r-oldrel

arm64

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

TensorPreAve archive

Depends

R ≥ 2.10

Imports

rTensor
MASS
stats
pracma

Suggests

knitr
rmarkdown