A new discrete-time autoregressive model (CIAR) is proposed for irregular time series; it is shown to be weakly stationary, admits a state-space representation for Kalman estimation, and is applied to stellar light curves for model checking and forecasting.
R., Bryant, G., Snook, I
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Discrete-time autoregressive model for unequally spaced time-series observations
A new discrete-time autoregressive model (CIAR) is proposed for irregular time series; it is shown to be weakly stationary, admits a state-space representation for Kalman estimation, and is applied to stellar light curves for model checking and forecasting.