Computational and statistical efficiency of semiparametric gls estimators
报告了半参数广义最小二乘估计计算效率的显著提升，并修正了之前论文中标准误的数值错误，修正后的标准误与分位数估计相当。
In this note, we report a dramatic improvement in the computational efficiency of semiparametric generalized least squares(SGLS) estimation. Computation of SGLS estimates no longer presents serious problems with data sets of moderate size. We also correct a numerical error in the standard errors of the SGLS estimates reported in our recent paper in this journal (Horowitz and Neumann, 1987). The corrected standard errors of SGLS are comparable to those we reported for quantile estimates.