PARAMETRIC LINK MODIFICATION OF BOTH TAILS IN BINARY REGRESSION
PARAMETRIC LINK MODIFICATION OF BOTH TAILS IN BINARY REGRESSION
复制标题
DOI：
10.1007/bf02926413
复制
发表时间：
1994-09-01
影响因子：
1.3
通讯作者：
CZADO, C
中科院分区：
文献类型：
--
作者：
CZADO, C
常用的二元回归模型，如Logistic回归或Probit回归，已经扩展到包括参数链接变换族。这些带有参数链接的二元回归模型是为了避免可能的链接错误说明而设计的，并提高了对某些数据集的拟合程度。文献中已经提出了单参数和双参数链接族(综述见Stukel(1988))。然而，在到目前为止公布的实际数据例子中，只有一个参数链接族发现显着改善了拟合。本文介绍了一个两参数链接族，它涉及对链节的两个尾部进行修改。给出了一种基于易于计算的贝叶斯推理的分析方法，该方法涉及蒙特卡罗抽样算法，推广了Zazado(1992,1993b)的早期工作。最后，将通过使用双尾修改显著改进单尾修改的例子来演示双尾链接修改的有用性。
Common binary regression models such as logistic or probit regression have been extended to include parametric link transformation families. These binary regression models with parametric link are designed to avoid possible link misspecification and improve fit in some data sets. One and two parameter link families have been proposed in the literature (for a review see Stukel (1988)). However in real data examples published so far only one parameter link families have found to improve the fit significantly. This paper introduces a two parameter link family involving the modification of both tails of the link. An analysis based on computationally tractable Bayesian inference involving Monte Carlo sampling algorithms is presented extending earlier work of Czado (1992, 1993b). Finally, the usefulness of the two tailed link modification will be demonstrated in an example where single tail modification can be significantly improved upon by using a two tailed modification.