Correlograms for non-stationary autoregressions
AbstractAnalysis 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. Copyright 2006 Royal Statistical Society.
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Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series B (Statistical Methodology).
Volume (Year): 68 (2006)
Issue (Month): 4 ()
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Other versions of this item:
- Bent Nielsen, 2003. "Correlograms for non-stationary autoregressions," Economics Papers 2003-W11, Economics Group, Nuffield College, University of Oxford.
- Bent Nielsen, 2003. "Correlograms for non-stationary autoregressions," Economics Series Working Papers 2003-W11, University of Oxford, Department of Economics.
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