利用IERS(International Earth Rotation and Reference Systems Service)发布的EOP 14 C04产品中1984~2022年LOD实测值进行频谱分析及周期项提取,并采用最小二乘外推模型联合多项式曲线拟合模型方法将提取到的周期项应用于对LOD序列的...利用IERS(International Earth Rotation and Reference Systems Service)发布的EOP 14 C04产品中1984~2022年LOD实测值进行频谱分析及周期项提取,并采用最小二乘外推模型联合多项式曲线拟合模型方法将提取到的周期项应用于对LOD序列的拟合。实验结果表明,相比于单一的LS外推模型拟合,新方法拟合序列的RMSE从0.0003 s下降至0.0001 s,且新方法将确定系数从0.80提高到0.97左右。该研究结果可为LOD序列的预报研究提供参考。展开更多
In 1980's, differential geometric methods are successfully used to study curved exponential families and normal nonlinear repression models. This paper presents a new geometric structure to study multinomial distr...In 1980's, differential geometric methods are successfully used to study curved exponential families and normal nonlinear repression models. This paper presents a new geometric structure to study multinomial distributipn models which contain a set of nonlinear parameters. Based on this geometric structure, the authors study several asymptotic properties for sequential estimation. The bias, the variance and the information loss of the sequeatial estimates are given from geometric viewpoint, and a limit theorem connected with the obServed and expected Fisher information is obtained ill terms of curVature measures. The results show that the sequeotial estimation procedure has some better properties which are generally impossible for nonsequeotial estimation procedures.展开更多
文摘In 1980's, differential geometric methods are successfully used to study curved exponential families and normal nonlinear repression models. This paper presents a new geometric structure to study multinomial distributipn models which contain a set of nonlinear parameters. Based on this geometric structure, the authors study several asymptotic properties for sequential estimation. The bias, the variance and the information loss of the sequeatial estimates are given from geometric viewpoint, and a limit theorem connected with the obServed and expected Fisher information is obtained ill terms of curVature measures. The results show that the sequeotial estimation procedure has some better properties which are generally impossible for nonsequeotial estimation procedures.