可加模型中参数的经验欧氏似然估计

The Emperical euclidean Likelihood Estimation about Parameters for the Additive Model

可加模型是参数设计中一个非常重要,实用的模型。本文讨论了可加模型中参数的经验欧氏似然估计及其性质,并给出了一种与参数的经验欧氏似然估计渐近等效的加权LS估计,最后分析了一个数值例子。

The additive model is one of the most important models in parameter design. In this paper, we discuss the empirical Euclidean likelihood estimation about parameters for the additive model. We also give WLS estimates of parameter vector for the additive model. The empirical Euclidean likelihood estimation about parameters is asymptotically as efficient as the WLS estimates. Finally, a numerical example is given.