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受约束二元线性回归系数的截断极大似然估计AI 解读

In a bivariate linear regression model, the constrained maximum likelihood estimator (MLE) of a regression coefficient usually has smaller variance than the unconstrained MLE. This situation can be reversed if both the sample size n and the correlation coefficient ρ of disturbances between two regression equations are small. That is, when both n and ρ are small, the variance of the unconstrained MLE is smaller than the constrained MLE. In this article, a truncated MLE is…

受约束双变量线性回归系数的截断极大似然估计AI 解读

In a bivariate linear regression model, the constrained maximum likelihood estimator (MLE) of a regression coefficient usually has smaller variance than the unconstrained MLE. This situation can be reversed if both the sample size n and the correlation coefficient ρ of disturbances between two regression equations are small. That is, when both n and ρ are small, the variance of the unconstrained MLE is smaller than the constrained MLE. In this article, a truncated MLE is…