An Improved Version of the Quandt-Ramsey MGF Estimator for Mixtures of Normal Distributions and Switching Regressions
改进了Quandt和Ramsey提出的正态混合与转换回归估计量，通过最小化广义平方和而非普通平方和，使得使用更多评估点（矩）明确优于较少点，结果也适用于一般矩估计方法。
Quandt and Ramsey have suggested an estimator for normal mixtures and switching regressions, which minimizes a sum of squared differences between empirical and theoretical values of the moment generating function. This paper demonstrates how their estimator can be improved by minimizing a generalized sum of squares rather than an ordinary sum of squares. When this is done, more points of evaluation (moments) are unambiguously better than less. Most of the results presented are also applicable to method of moments estimators in general.