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Estimation and hypothesis testing in BIB design and robustness

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  • Tiku, Moti L.
  • Senoglu, Birdal

Abstract

Modified maximum likelihood estimators of the unknown parameters in a BIB design under non-normality of error distributions are obtained. They are shown to be more efficient and robust than the traditional least squares estimators. A test statistic for testing a linear contrast among treatment effects is developed. A real life example is given.

Suggested Citation

  • Tiku, Moti L. & Senoglu, Birdal, 2009. "Estimation and hypothesis testing in BIB design and robustness," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3439-3451, July.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:9:p:3439-3451
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    References listed on IDEAS

    as
    1. Bi-super-˙rdal Senoğlu, 2005. "Robust 2k factorial design with Weibull error distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(10), pages 1051-1066.
    2. Tiku, Moti L. & Islam, M. Qamarul & Sazak, Hakan S., 2008. "Estimation in bivariate nonnormal distributions with stochastic variance functions," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1728-1745, January.
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