Maximum Likelihood Estimation Methods for Variance Components in Linear Non-Orthogonal Small Size Design Models
We compare four Maximum Likelihood Estimation methods for estimating variance components in normal linear mixed models, in the case of unbalanced small size design models: The Newton-Raphson, the Triple Minimization, the Gradient and a method where the starting points for the Newton-Raphson are the...
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| Other Authors: | , , |
| Format: | article |
| Language: | eng |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10400.6/9168 |
| Country: | Portugal |
| Oai: | oai:ubibliorum.ubi.pt:10400.6/9168 |
| Summary: | We compare four Maximum Likelihood Estimation methods for estimating variance components in normal linear mixed models, in the case of unbalanced small size design models: The Newton-Raphson, the Triple Minimization, the Gradient and a method where the starting points for the Newton-Raphson are the estimates obtained with the Triple Minimization method. |
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