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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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2017
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| Online Access: | http://journalarticle.ukm.my/10685/1/17%20Adilah%20Abdul%20Ghapor.pdf http://journalarticle.ukm.my/10685/ http://www.ukm.my/jsm/english_journals/vol46num2_2017/contentsVol46num2_2017.html |
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