Missing value estimation methods for data in linear
functional relationship model

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Missing value estimation methods for data in linear functional relationship model

Missing value problem is common when analysing quantitative data. With the rapid growth of computing capabilities, advanced methods in particular those based on maximum likelihood estimation has been suggested to best handle the missing values problem. In this paper, two modern imputing approaches n...

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Bibliographic Details
Main Authors:	Adilah Abdul Ghapor, Yong Zulina Zubairi, A.H.M. Rahmatullah Imon
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2017
Online Access:	http://journalarticle.ukm.my/10685/ http://journalarticle.ukm.my/10685/1/17%20Adilah%20Abdul%20Ghapor.pdf

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