The Conditions with Different Models Having Identical Predictions
In linear mixed models theory one is assumed to know the structure of random effects covariance matrix. The suggestions are sometimes contradictious, especially if the model includes interactions between fixed effects and random effects. Mols (2003) presented conditions under which two different random effects variance matrices will yield equal estimation and prediction results during the paper it is assumed that X is of full column rank. Wang (2010 1 1 ) weakened the conditions of his theorem, and obtained the same results as his. Wang (2010(12)) extended Molss (2003) results to situation that X is deficient in rank. We give a series of results in the paper it is assumed that X is possibly deficient in rank. They contain some necessary and sufficient theorems.
linear mixed models best linear unbiased estimator best linear unbiased predictor robustly predictable mean square error.
Shiqing Wang Ying Ma
College of Mathematics and Information Sciences, North China University of Water Conservancy and Electric Power, Zhengzhou, 450011, China
国际会议
南京
英文
183-186
2010-07-29（万方平台首次上网日期，不代表论文的发表时间）