AIMS:Average Information Matrix Splitting
Methodology
2020-05-11 v4 Numerical Analysis
Numerical Analysis
Abstract
For linear mixed models with co-variance matrices which are not linearly dependent on variance component parameters, we prove that the average of the observed information and the Fisher information can be split into two parts. The essential part enjoys a simple and computational friendly formula, while the other part which involves a lot of computations is a random zero matrix and thus is negligible.
Cite
@article{arxiv.1605.07646,
title = {AIMS:Average Information Matrix Splitting},
author = {Shengxin Zhu and Tongxiang Gu and Xingping Liu},
journal= {arXiv preprint arXiv:1605.07646},
year = {2020}
}