Package: PanelTM 1.1

F. Marta L. Di Lascio

PanelTM: Two- And Three-Way Dynamic Panel Threshold Regression Model for Change Point Detection

Estimation of two- and three-way dynamic panel threshold regression models (Di Lascio and Perazzini (2024) <https://repec.unibz.it/bemps104.pdf>; Di Lascio and Perazzini (2022, ISBN:978-88-9193-231-0); Seo and Shin (2016) <doi:10.1016/j.jeconom.2016.03.005>) through the generalized method of moments based on the first difference transformation and the use of instrumental variables. The models can be used to find a change point detection in the time series. In addition, random number generation is also implemented.

Authors:Selene Perazzini [aut], F. Marta L. Di Lascio [aut, cre]

PanelTM_1.1.tar.gz
PanelTM_1.1.tar.gz(r-4.7-any)PanelTM_1.1.tar.gz(r-4.6-any)
PanelTM_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
PanelTM/json (API)

# Install 'PanelTM' in R:
install.packages('PanelTM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • banana - Biompedance measurements on bananas.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 2 stars 169 downloads 5 exports 2 dependencies

Last updated from:e5c3c3ffab. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK111
source / vignettesOK161
linux-release-x86_64OK111
wasm-releaseOK101

Exports:cpointperfmptm2ptm3simptm

Dependencies:MASSpracma