| 1. | Optimal experimental designs for the generalized multivariate linear model 广义多元线性模型的最优设计 |
| 2. | Posterior likelihood ratio tests for multivariate linear model based on normal - inverse wishart prior 先验信息下多元线性模型的后验似然比检验 |
| 3. | Extension of the uniformly minimum variance unbiased estimation of a class of multivariate linear model 一类多元线性模型的一致最小方差无偏估计的推广 |
| 4. | Admissibility of linear estimation of multivariate linear model with respect to a restricted parameter set 带有不完全椭球约束的多元线性模型中线性估计的可容许性 |
| 5. | The general growth curve model is a more generalized multivariate linear model that is widely applied in biology , technology substitutions and economic forecast , ect 一般增长曲线模型是更为广泛的线性模型,这一模型在许多领域如生物学、医学、工艺替代、经济预测等方面都有重要应用 |
| 6. | For the general multivariate linear model , in this paper , the necessary and sufficient condition for admissibility of the linear estimator for sx in the class of linear estimator under different criteria is gained 摘要对于一般未知方差多元线性模型,讨论了共同均值矩阵参数的可估函数sx的线性估计在线性估计类中的可容许性问题,证明了在本文所给的不同优良准则下可容许性是等价的,并得到了它们的充要条件。 |
| 7. | Based on the comprehensive analysis of the road traffic flow ' s characteristics due to the bus stop without bus bay , the multivariate linear models of the speed and the headway are formed with the variables of the stop frequency , the stop time , the overall length of the stop and its reserve time of the bus and the vehicle flow applying the software of excel , and then the strict mathematical checks are made 文章首先比较全面地分析非港湾式公交停车影响下道路交通流特徵,然后借助于excel软件,构建关于公交停车频率、公交停车时间、最大公交停车长度及其存在时间、道路流量的车速和车头时距多元线性模型,并进行了严格的数学检验。 |
| 8. | One is to derive the optimal prediction and the other is to find its necessary and sufficient conditions . there is , however , a more design matrix in this model than is in multivariate linear model , which has caused difficulties such as solving a exceptional unlinear matrix equation groups especially when deriving the optimal prediction 但是因为一般增长曲线模型比多元线性模型多一个设计阵,这就给研究带来了很大的困难,特别是在求解模型的最优预测时,遇到了一类特殊的非线性矩阵方程组,所以在一般情况下我们既无法求出模型的最优预测,也无法找到存在最优预测的充要条件 |