COMPUTATION OF MAXIMUM LIKELIHOOD ESTIMATES OF GRAVITY MODEL PARAMETERS*
推导了多种新算法来计算广义引力模型参数的最大似然估计，并与GLIM等旧算法比较，发现一种新算法在速度和稳健性上显著优于其他方法。
ABSTRACT. This paper presents the derivations of several new algorithms for the computation of maximum likelihood estimates of the parameters of a very general form of the gravity model. The algorithms are then compared with previously available algorithms including GLIM and that given in Sen (1986). One of the new algorithms emerges as far superior in just about every way to its competitors. In particular, it is usually much more than an order of magnitude faster than the GLIM procedure and that given in Sen (1986). It is also not substantially affected by pitfalls such as multicollinearity and (unlike the GLIM procedure) is capable of comfortably handling large O‐D matrices.