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Deletion diagnostics for transformations of time series

โœ Scribed by A. C. Atkinson; Neil Shephard


Publisher
John Wiley and Sons
Year
1996
Tongue
English
Weight
917 KB
Volume
15
Category
Article
ISSN
0277-6693

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โœฆ Synopsis


Deletion diagnostics are derived for the effect of individual observations on the estimated transformation of a time series. The paper uses the modified power transformation of Box and Cox to provide a paramemc family of transformations. Inference about the transformation parameter is made through regression on a constructed variable. The effect of deletion of observations on residuals and on the estimate of the regression parameter are obtained. Index plots of the diagnostic quantities are shown to be highly informative. Structural time series modelling is used, so that the results readily extend to inference about regression on other explanatory variables.


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A simple recursion is presented for calculating moments (e.g., mean, variance, and autocorrelation function) of a time series that has been power transformed to normality. Its derivation is elementary, relying on the moment-generating function for a bivariate normal distribution. To make clear the d