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- W2737096810 abstract "In this presentation, we propose a goodness-of-fit test of normality for the errors of an ARMA(p,q) model with unknown mean. The orders p and q are supposed to be known and will be fixed. The test is based on the data-driven Neyman smooth test approach and is simple to perform. A simulation study will show how the test performs for small to moderate sample sizes. We will try to show how this procedure can be extended to other situations, such as, for example, more sophisticated models or to a multivariate framework." @default.
- W2737096810 created "2017-07-31" @default.
- W2737096810 creator A5021848861 @default.
- W2737096810 date "2008-05-25" @default.
- W2737096810 modified "2023-10-16" @default.
- W2737096810 title "Multi- and univariate Neyman smooth test of normality in a time series context" @default.
- W2737096810 hasPublicationYear "2008" @default.
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