Linear Contrasts for Time Series Data with Non-Normal Innovations: An Application to a Real Life Data

2017-12-08
Yıldırım, Özgecan
Yozgatlıgil, Ceylan
Şenoğlu, Birdal
Yıldırım et al. [5] estimated the model parameters and introduced a test statistic in one-way classification AR(1) model under the assumption of independently and identically distributed (iid) error terms having Student’s t distribution, see also [4]. In this study, we extend their study to linear contrasts which is a well-known and widely used comparison method when the null hypothesis about the equality of the treatment means is rejected, see [3], [4]. See also [1] and [2] in the context of ANOVA. A test statistic for the linear contrasts is introduced. A comprehensive simulation study is done to compare the performance of the test statistic with the corresponding normal theory test statistic. At the end of the study, a real life data is analysed to show the implementation of the introduced test statistic.
10.International Statistics Congress (ISC2017), (December 6-8 2017)

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Citation Formats
Ö. Yıldırım, C. Yozgatlıgil, and B. Şenoğlu, “Linear Contrasts for Time Series Data with Non-Normal Innovations: An Application to a Real Life Data,” presented at the 10.International Statistics Congress (ISC2017), (December 6-8 2017), Ankara, Türkiye, 2017, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/75885.