A NON-ITERATIVE LEAST SQUARES ESTIMATION OF MISSING DATA IN RECTANGULAR LATTICE DESIGNS

Abimibola Victoria Oladugba; Emmanuel Ogochukwu Ossai

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A NON-ITERATIVE LEAST SQUARES ESTIMATION OF MISSING DATA IN RECTANGULAR LATTICE DESIGNS

Author(s)

Abimibola Victoria Oladugba Department of Statistics, University of Nigeria,Nsukka,Nigeria

Emmanuel Ogochukwu Ossai Department of Statistics, University of Nigeria,Nsukka,Nigeria

Abstract

Missing data are inevitable problem in almost every research such as experimental and observational researches. In this paper, we proposed a non-iterative least square formulae for estimating missing data in rectangular lattice designs (simple and triple) without repetitions of the basic design using the intra-block information when one or more observations are missing. A numerical example was used to show the applicability of the proposed formulae in terms of estimated values, standard errors and p-value. Results showed that the estimated values were significantly approximate to the complete data which indicate the effectiveness of the proposed formulae for estimating missing data in rectangular lattice designs without repetitions.

Publication Details

Page(s) 207-224

DOI DOI not available

Published Journal: Pakistan Journal of Statistics, Volume: 36, Issue: 3, Year: 2020

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Keywords

repetition, treatments, bias, missing data, Rectangular lattice designs, non-iterative least square estimate

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