Analysis of variance and linear contrasts in experimental design with generalized secant hyperbolic distribution

Date

2008-07-01

Author

Yilmaz, Yidiz E.
Akkaya, Ahmet

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We consider one-way classification model in experimental design when the errors have generalized secant hyperbolic distribution. We obtain efficient and robust estimators for block effects by using the modified maximum likelihood estimation (MML) methodology. A test statistic analogous to the normal-theory F statistic is defined to test block effects. We also define a test statistic for testing linear contrasts. It is shown that test statistics based on MML estimators are efficient and robust. The methodology readily extends to unbalanced designs.

Subject Keywords

Applied Mathematics, Computational Mathematics

URI

https://hdl.handle.net/11511/41631

Collections

Department of Political Science and Public Administration, Article