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• W2900182504 abstract "The paper considers the problem of testing for normality of the one-dimensional marginal distribution of a strictly stationary and weakly dependent stochastic process. The possibility of using an autoregressive sieve bootstrap procedure to obtain critical values and P-values for normality tests is explored. The small-sample properties of a variety of tests are investigated in an extensive set of Monte Carlo experiments. The bootstrap version of the classical skewness–kurtosis test is shown to have the best overall performance in small samples." @default.
• W2900182504 created "2018-11-16" @default.
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• W2900182504 date "2017-01-01" @default.
• W2900182504 modified "2023-10-16" @default.
• W2900182504 title "Normality Tests for Dependent Data" @default.
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• W2900182504 hasPublicationYear "2017" @default.
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