Conditional independence models for seemingly unrelated regressions with incomplete data

JOURNAL OF MULTIVARIATE ANALYSIS

卷:97

Article

Drton, M ; Andersson, SA ; Perlman, MD

关键词: acyclic directed graph;    graphical model;    incomplete data;    lattice conditional independence model;    MANOVA;    maximum likelihood estimator;    multivariate analysis;    missing data;    seemingly unrelated regressions;   

DOI  :  10.1016/j.jmva.2005.03.014

来源: Elsevier

【 摘 要 】

We consider normal = Gaussian seemingly unrelated regressions (SUR) with incomplete data (ID). Imposing a natural minimal set of conditional independence constraints, we find a restricted SUR/ID model whose likelihood function and parameter space factor into the product of the likelihood functions and the parameter spaces of standard complete data multivariate analysis of variance models. Hence, the restricted model has a unimodal likelihood and permits explicit likelihood inference. In the development of our methodology, we review and extend existing results for complete data SUR models and the multivariate ID problem. (C) 2005 Elsevier Inc. All rights reserved.

【 授权许可】

Free