ESTIMATING THE MISSING VALUE IN ONE-WAY ANOVA UNDER LONG-TAILED SYMMETRIC ERROR DISTRIBUTIONS

Authors : Demet AYDIN, Birdal ŞENOĞLU

Pages : 523-538

View : 29 | Download : 11

Publication Date : 2018-06-01

Article Type : Research Paper

Abstract :In practice, missing values are widely seen and create serious problems in almost all statistical analysis. In this study, to deal with missing values, we propose estimators for missing value in one-way analysis of variance insert ignore into journalissuearticles values(ANOVA); when the distribution of error terms is long-tailed symmetric insert ignore into journalissuearticles values(LTS);. We use methodologies known as maximum likelihood insert ignore into journalissuearticles values(ML);, modified maximum likelihood insert ignore into journalissuearticles values(MML); and least squares insert ignore into journalissuearticles values(LS); in estimating missing value. Expectation and maximization insert ignore into journalissuearticles values(EM); algorithm is used for computing ML estimate of missing value. We compare the efficiencies of LS, ML and MML estimators of missing value via Monte Carlo simulation study. Simulation results show that ML estimator of missing value is the most efficient among the others. The usefulness of the proposed estimators is illustrated by peak discharge data example taken from civil engineering.
Keywords : Missing value, one way ANOVA, LTS distribution, EM algorithm, MML methodology

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