Abstract
The application of autoregressive moving-average (ARMA) modelling to discrete time or indexed data is discussed. An essential tool is the autocorrelation function, and its utility is demonstrated with some examples. Extensions of the ARMA models to include non-stationarity are described; variability in both the series mean and the ARMA coefficients can be dealt with by recursively calculated or state space models. A number of tests for non-stationarity of the series mean are described in detail. Particular attention is devoted to the effects of serial dependence of the data. A problem with the O-C (observed-calculated) method as traditionally used in astronomy is pointed out
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call