On discrimination and classification with multivariate repeated measures data
On discrimination and classification with multivariate repeated measures data
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DOI：
10.1016/j.jspi.2004.04.012
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发表时间：
2005-10-01
影响因子：
0.9
通讯作者：
Khattree, R
中科院分区：
文献类型：
--
作者：
Roy, A;Khattree, R
本文研究了多个q变量观测值的分类问题，其中每个个体有时间效应和没有时间效应。我们开发了新的分类规则的人口与某些结构化和非结构化的平均向量，并在一定的协方差结构。新的分类规则是有效的，当观测值的数量不足以估计方差-协方差矩阵。所需的人口参数的最大似然估计的计算方案。我们将我们的研究结果应用到两个真实的数据集以及模拟数据集。(c)2004 Elsevier B. V.保留所有权利。
We study the problem of classification with multiple q-variate observations with and without time effect on each individual. We develop new classification rules for populations with certain structured and unstructured mean vectors and under certain covariance structures. The new classification rules are effective when the number of observations is not large enough to estimate the variance-covariance matrix. Computational schemes for maximum likelihood estimates of required population parameters are given. We apply our findings to two real data sets as well as to a simulated data set. (c) 2004 Elsevier B.V. All rights reserved.