iar 1.2.8

Irregularly Observed Autoregressive Models

iAR package

Description

Data sets, functions and scripts with examples to implement autoregressive models for irregularly observed time series. The models available in this package are the irregular autoregressive model (Eyheramendy et al.(2018)), the complex irregular autoregressive model (Elorrieta et al.(2019)) and the bivariate irregular autoregressive model (Elorrieta et al.(2021)).

Contents

• Irregular Autoregressive (IAR) Model [1]
• Complex Irregular Autoregressive (CIAR) Model [2]
• Bivariate Irregular Autoregressive (BIAR) Model [3]

Instalation

Dependencies:

numpy
pandas
scipy
matplotlib
sklearn
statsmodels

Install from PyPI using:

pip install iar

or clone this github and do:

python setup.py install --user

Examples

• IAR Model demo here
• CIAR Model demo here
• BIAR Model demo here

Authors

• Felipe Elorrieta ([e-mail]) (Millennium Institute of Astrophysics and Universidad de Santiago de Chile)
• Cesar Ojeda (Universidad del Valle - Colombia)
• Susana Eyheramendy (Millennium Institute of Astrophysics and Universidad Adolfo Ibañez)
• Wilfredo Palma (Millennium Institute of Astrophysics)

Acknowledgments

The authors acknowledge support from the ANID – Millennium Science Initiative Program – ICN12_009 awarded to the Millennium Institute of Astrophysics MAS (www.astrofisicamas.cl)

References

[1] Eyheramendy S, Elorrieta F, Palma W (2018). “An irregular discrete time series model to identify residuals with autocorrelation in astronomical light curves.” Monthly Notices of the Royal Astronomical Society, 481(4), 4311–4322. ISSN 0035-8711, doi: 10.1093/mnras/sty2487, https://academic.oup.com/mnras/article-pdf/481/4/4311/25906473/sty2487.pdf.

[2] Elorrieta, F, Eyheramendy, S, Palma, W (2019). “Discrete-time autoregressive model for unequally spaced time-series observations.” A& A, 627, A120. doi: 10.1051/00046361/201935560, https://doi.org/10.1051/0004-6361/201935560.

[3] Elorrieta, F, Eyheramendy, S, Palma, W, Ojeda, C (2021).A novel bivariate autoregressive model for predicting and forecasting irregularly observed time series, Monthly Notices of the Royal Astronomical Society, 505 (1),1105–1116,https://doi.org/10.1093/mnras/stab1216

[4] Jordán A, Espinoza N, Rabus M, Eyheramendy S, Sing DK, Désert J, Bakos GÁ, Fortney JJ, LópezMorales M, Maxted PFL, Triaud AHMJ, Szentgyorgyi A (2013). “A Ground-based Optical Transmission Spectrum of WASP-6b.” The Astrophysical Journal, 778, 184. doi: 10.1088/0004637X/ 778/2/184, 1310.6048, https://doi.org/10.1088/0004-637X/778/2/184.

[5] Lira P, Arévalo P, Uttley P, McHardy IMM, Videla L (2015). “Long-term monitoring of the archetype Seyfert galaxy MCG-6-30-15: X-ray, optical and near-IR variability of the corona, disc and torus.” Monthly Notices of the Royal Astronomical Society, 454(1), 368–379. ISSN 0035-8711, doi: 10.1093/mnras/stv1945, https://doi.org/10.1093/mnras/stv1945.