# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "statioVAR" in publications use:' type: software license: GPL-3.0-only title: 'statioVAR: Trend Removal for Vector Autoregressive Workflows' version: 0.1.3 identifiers: - type: doi value: 10.32614/CRAN.package.statioVAR abstract: Detrending multivariate time-series to approximate stationarity when dealing with intensive longitudinal data, prior to Vector Autoregressive (VAR) or multilevel-VAR estimation. Classical VAR assumes weak stationarity (constant first two moments), and deterministic trends inflate spurious autocorrelation, biasing Granger-causality and impulse-response analyses. All functions operate on raw panel data and write detrended columns back to the data set, but differ in the level at which the trend is estimated. See, for instance, Wang & Maxwell (2015) ; Burger et al. (2022) ; Epskamp et al. (2018) . authors: - family-names: Corbelli given-names: Giuseppe email: giuseppe.corbelli@uniroma1.it orcid: https://orcid.org/0000-0002-2864-3548 preferred-citation: type: manual title: 'statioVAR: Trend Removal for Vector Autoregressive Workflows' authors: - family-names: Corbelli given-names: Giuseppe email: giuseppe.corbelli@uniroma1.it orcid: https://orcid.org/0000-0002-2864-3548 year: '2025' notes: R package version 0.1.1 url: https://github.com/g-corbelli/statioVAR repository: https://cran.r-universe.dev repository-code: https://github.com/g-corbelli/statioVAR commit: 3231e373c4738d90ec85c69a8f3e143c8158acee url: https://github.com/g-corbelli/statioVAR date-released: '2025-08-20' contact: - family-names: Corbelli given-names: Giuseppe email: giuseppe.corbelli@uniroma1.it orcid: https://orcid.org/0000-0002-2864-3548