Estimates for a Regression Parameter Using Ranks
研究了部分指定模型中回归参数的估计，该模型经未知单调递增变换后响应变量服从正态分布并与解释变量呈线性关系，比较了Doksum重抽样技术及其修改、Fisher-Yates正态得分法修改和秩均值估计的效果。
SUMMARY In this paper we consider the estimation of a regression parameter in a partially specified model where, after an unknown monotone increasing transformation, the response is normally distributed and related to an explanatory variable by a linear model. We consider a Monte Carlo resampling technique due to Doksum and various modifications of it. In addition a simple estimate based on a modification of Fisher and Yates' normal scores method and an estimate using the means of ranks are considered. The estimates are compared using simulation.