When fitting a Gaussian mixture regression model to observed data, estimating a between-group contrast can be a practical issue. One can use the estimate to compare the effects of a particular covariate or a set of covariates across different subpopulations. By applying fiducial generalized pivotal quantities, a small-sample solution is proposed in this paper to obtain interval estimates of between-group contrasts. Specifically, a Markov chain Monte Carlo sampler, which takes the membership uncertainty of each individual into account, is designed to generate realizations from the target distributions for computing the required interval estimates. A plant virus transmission study is first introduced as a motivating example for the present study. Next, the observed data are analyzed to illustrate the proposed method. Based on the simulation results, it is further shown that the proposed method can maintain the empirical coverage rates sufficiently close to the nominal level.Supplementary materials accompanying this paper appear on-line.

中文翻译：

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比较高斯混合回归模型中亚群的系数

在将高斯混合回归模型拟合到观测数据时，估计组间对比度可能是一个实际问题。可以使用估计来比较特定协变量或一组协变量对不同亚群的影响。通过应用基准广义关键量，本文提出了一种小样本解决方案，以获得组间对比的区间估计。具体而言，马尔可夫链蒙特卡罗采样器将每个人的成员资格不确定性考虑在内，旨在从目标分布生成实现，以计算所需的区间估计。首先介绍植物病毒传播研究作为本研究的激励示例。接下来，分析观察到的数据以说明所提出的方法。根据仿真结果，