Irregularly Observed Autoregressive Models

Data sets and functions for implementing discrete-time autoregressive models for irregularly observed time series. The models implemented include the irregular autoregressive (iAR) model (Eyheramendy et al. (2018) ), the complex irregular autoregressive (CiAR) model (Elorrieta et al. (2019) ), and the bivariate irregular autoregressive (BiAR) model (Elorrieta et al. (2021) ). For a comprehensive description of the package and its applications, see Elorrieta et al. (2026) .

iAR

Description

Data sets and functions for implementing discrete-time autoregressive models for irregularly observed time series. The models implemented include the irregular autoregressive (iAR) model (Eyheramendy et al., 2018), the complex irregular autoregressive (CiAR) model (Elorrieta et al., 2019), and the bivariate irregular autoregressive (BiAR) model (Elorrieta et al., 2021). For a comprehensive description of the package and its applications, see Elorrieta et al. (2026), published in The R Journal.

Installation

You can install the released version of iAR from Github with:

remotes::install_github("felipeelorrieta/iAR-package")

Code of Conduct

Please note that the iAR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.