A new expectation-maximization（EM） algorithm is proposed to estimate the parameters of the truncated multinormal distribution with linear restriction on the variables. Compared with the generalized method of moments...A new expectation-maximization（EM） algorithm is proposed to estimate the parameters of the truncated multinormal distribution with linear restriction on the variables. Compared with the generalized method of moments（GMM） estimation and the maximum likelihood estimation（MLE） for the truncated multivariate normal distribution, the EM algorithm features in fast calculation and high accuracy which are shown in the simulation results. For the real data of the national college entrance exams（NCEE）, we estimate the distribution of the NCEE examinees＇ scores in Anhui, 2003, who were admitted to the university of science and technology of China（USTC）. Based on our analysis, we have also given the ratio truncated by the NCEE admission line of USTC in Anhui, 2003.展开更多
基金Supported by the National Natural Science Foundation(Grant No.11571337,11271347,71172214)
文摘A new expectation-maximization（EM） algorithm is proposed to estimate the parameters of the truncated multinormal distribution with linear restriction on the variables. Compared with the generalized method of moments（GMM） estimation and the maximum likelihood estimation（MLE） for the truncated multivariate normal distribution, the EM algorithm features in fast calculation and high accuracy which are shown in the simulation results. For the real data of the national college entrance exams（NCEE）, we estimate the distribution of the NCEE examinees＇ scores in Anhui, 2003, who were admitted to the university of science and technology of China（USTC）. Based on our analysis, we have also given the ratio truncated by the NCEE admission line of USTC in Anhui, 2003.
