The Computation of FIML Estimates as Iterative Generalized Least Squares Estimates in Linear and Nonlinear Simultaneous Equations Models
线性与非线性联立方程模型中全信息极大似然估计的迭代广义最小二乘计算
THE PURPOSE OF THIS PAPER is threefold: (i) to provide a unified iterative generalized least squares approach for computing FIML estimates for both linear and nonlinear simultaneous equations models of medium size (containing about 50 parameters in the nonlinear case and 75 in the linear case); (ii) to suggest a useful procedure to determine the length of the step to be made at each iteration of the algorithm; (iii) to report on numerical results which illustrate the…