Bibliography

Belcher, J.; Hampton, J. S. and Wilson, G. T. (1994). Parameterization of Continuous Time Autoregressive Models for Irregularly Sampled Time Series Data. Journal of the Royal Statistical Society. Series B (Methodological) 56, 141–155. Accessed on Jun 2, 2023.

Jones, R. H. (1981). FITTING A CONTINUOUS TIME AUTOREGRESSION TO DISCRETE DATA. In: Applied Time Series Analysis II, edited by FINDLEY, D. F. (Academic Press); pp. 651–682.

Jones, R. H. and Ackerson, L. M. (1990). Serial Correlation in Unequally Spaced Longitudinal Data. Biometrika 77, 721–731. Accessed on Jun 2, 2023.

Foreman-Mackey, D.; Agol, E.; Ambikasaran, S. and Angus, R. (2017). Fast and Scalable Gaussian Process Modeling with Applications to Astronomical Time Series. The Astrophysical Journal 154, 220, arXiv:1703.09710 [astro-ph.IM].

Kelly, B. C.; Becker, A. C.; Sobolewska, M.; Siemiginowska, A. and Uttley, P. (2014). Flexible and Scalable Methods for Quantifying Stochastic Variability in the Era of Massive Time-domain Astronomical Data Sets. The Astrophysical Journal 788, 33, arXiv:1402.5978 [astro-ph.IM].

Lefkir, M.; Vaughan, S.; Huppenkothen, D.; Uttley, P. and Anilkumar, V. (2025). Modelling variability power spectra of active galaxies from irregular time series. Monthly Notices of the Royal Astronomical Society 539, 1775–1795, arXiv:2501.05886 [astro-ph.GA].

Rasmussen, C. E. and Williams, C. K. (2006). Gaussian Processes for Machine Learning (The MIT Press).