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Augmented mixed beta regression models with skew-normal independent distributions: Bayesian analysis of labor force data

机译:具有偏正态独立分布的增强混合β回归模型:劳动力数据的贝叶斯分析

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摘要

Augmented mixed beta regression models are suitable choices for modeling continuous response variables on the closed interval [0, 1]. The random eeceeects in these models are typically assumed to be normally distributed, but this assumption is frequently violated in some applied studies. In this paper, an augmented mixed beta regression model with skew-normal independent distribution for random effects are used. Next, we adopt a Bayesian approach for parameter estimation using the MCMC algorithm. The methods are then evaluated using some intensive simulation studies. Finally, the proposed models have applied to analyze a dataset from an Iranian Labor Force Survey.
机译:增强的混合beta回归模型是在封闭区间[0,1]上建模连续响应变量的合适选择。这些模型中的随机效应通常被假定为正态分布,但是在某些应用研究中经常违反这一假设。在本文中,使用具有偏态正态独立分布的增强混合β回归模型来产生随机效应。接下来,我们采用贝叶斯方法进行MCMC算法的参数估计。然后使用一些深入的模拟研究对方法进行评估。最后,提出的模型已用于分析来自伊朗劳动力调查的数据集。

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