Abstract
The aim of this article is to present an estimation procedure for both fixed effects and variance components in linear mixed models. This procedure consists of a maximum-likelihood method which we call Three Step Minimization (TSM). The major contribution of this method is that when variances tend to be null standard algorithms behave badly, unlike the TSM method, which uses a grid search algorithm in a compact set. A numerical application with real and simulated data is provided.
Original language | English |
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Pages (from-to) | 1156-1166 |
Number of pages | 11 |
Journal | Communications in Statistics: Simulation and Computation |
Volume | 46 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2017 |
Keywords
- Inference
- Maximum-likelihood
- Mixed models
- Newton–Raphson
- Variance components