Correlograms for non-stationary autoregressions
Journal of the Royal Statistical Society: Series B (Statistical Methodology) · 2006 · Volume 68 · Issue 4
DOI: 10.1111/j.1467-9868.2006.00563.x
Abstract
Summary.Analysis of time series often involves correlograms and partial correlograms as graphical descriptions of temporal dependence. Two methods are available for computing these statistics: one based on autocorrelations and the other on scaled autocovariances. For a stationary time series the resulting plots are nearly identical. When it comes to time series exhibiting non-stationary features these methods can lead to very different results. This has two consequences: incorrect inferences can be drawn when confusing these concepts; better discrimination between stationary and non-stationarity is achieved when using autocorrelations instead of, or along with, the autocovariances which are commonly used in statistical software.
Keywords
Autoregression, Correlogram, Covariogram, Non-stationarity, Partial correlogram
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