Likelihood inference for small variance components
The authors explore likelihood-based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, they use local asymptotic approximations to construct conﬁdence intervals for the components of variance when the components are close to the boundary of the parameter space. In the process, they explore the question of how to proﬁle the restricted likelihood (REML). Also, they show that general REML estimates are less likely to fall on the...[Show more]
|Collections||ANU Research Publications|
|Source:||Canadian Journal of Statistics|
|smallvarcomp.pdf||201.8 kB||Adobe PDF|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.