On Estimating Variance Components of Two-Way Nested Random Model with Missing Information

Amany Mousa Mohammed; Ahmed Amin El-Sheikh; Alaa Sayed Shehata

doi:10.9734/ajpas/2018/v2i228777

Research Article Open access CC BY 4.0

On Estimating Variance Components of Two-Way Nested Random Model with Missing Information

Amany Mousa Mohammed, Ahmed Amin El-Sheikh, Alaa Sayed Shehata

Asian Journal of Probability and Statistics · pp. 1–14 · Published 20 Dec 2018

10.9734/ajpas/2018/v2i228777

Abstract

In this paper, the estimators of variance components are derived of two-way nested random model when the problem of missing information exists using combination between Modified Minimum Variance Quadratic Unbiased Estimation (MMIVQUE) and Modified Minimum Variance Quadratic Unbiased Estimation (MMIVQUE (0)) methods that is called MMIV(MIV(0)) method.

MINQUE missing information MIVQUE variance components

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Amany Mousa Mohammed, Ahmed Amin El-Sheikh, Alaa Sayed Shehata (2018). On Estimating Variance Components of Two-Way Nested Random Model with Missing Information. Asian Journal of Probability and Statistics , 1–14. https://doi.org/10.9734/ajpas/2018/v2i228777

Affiliations

Amany Mousa Mohammed — Department of Applied Statistics and Econometrics, Institute of Statistical Studies and Research, Cairo University, Egypt.
Ahmed Amin El-Sheikh — Department of Applied Statistics and Econometrics, Institute of Statistical Studies and Research, Cairo University, Egypt.
Alaa Sayed Shehata — Department of Applied Statistics and Econometrics, Institute of Statistical Studies and Research, Cairo University, Egypt.

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