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

Aydin D., ŞENOĞLU B.

SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, cilt.36, sa.2, ss.523-538, 2018 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 2
  • Basım Tarihi: 2018
  • Dergi Adı: SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Academic Search Premier, Directory of Open Access Journals
  • Sayfa Sayıları: ss.523-538
  • Anahtar Kelimeler: Missing value, one-way ANOVA, LTS distribution, EM algorithm, MML methodology, LEAST-SQUARES ESTIMATION, T-DISTRIBUTION, VARIANCE, TRANSFORMATIONS, LIKELIHOOD, IMPUTATION, NORMALITY, ALGORITHM
  • Ankara Üniversitesi Adresli: Evet

Özet

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 (ANOVA) when the distribution of error terms is long-tailed symmetric (LTS). We use methodologies known as maximum likelihood (ML), modified maximum likelihood (MML) and least squares (LS) in estimating missing value. Expectation and maximization (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.