The first is the full information maximum likelihood method with linear constraint of coefficient matrixes in structure equation.
结构方程系数矩阵线性约束下的完全信息极大似然估计法。
Conclusion the maximum likelihood method based on MCECM algorithm can be used to estimate the parameters of non-linear factor analysis model.
结论基于MCECM算法的极大似然估计方法可用于估计非线性因子分析模型的参数。
Parameters of the model are measured by a linear regression technique and a maximum likelihood method.
在因子范围服从对数正态分布下，应用线性回归技术和极大似然法建立了模型参数的测定方法。
A method for estimating the curves and their confidence bounds is developed by a linear regression technique and a maximum likelihood principle.
应用线性回归技术和极大似然法原理，给出了概率曲线及其置信限的估计方法。
A method for estimating the curves and their confidence bounds is developed by a linear regression technique and a maximum likelihood principle.
应用线性回归技术和极大似然法原理，给出了概率曲线及其置信限的估计方法。
应用推荐