首页> 外文期刊>Communications in Statistics >Augmented mixed beta regression models with skew-normal independent distributions: Bayesian analysis of labor force data
【24h】

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

机译:增强混合Beta回归模型具有偏斜正常的独立分布:贝叶斯劳动力数据分析

获取原文
获取原文并翻译 | 示例

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:增强混合Beta回归模型是用于在闭合间隔上建模连续响应变量的合适选择[0,1]。这些模型中的随机eEpeEcts通常假设通常分布,但在一些应用研究中经常违反这种假设。在本文中,使用了一种具有倾斜正常独立分布的随机效应的增强混合β回归模型。接下来,我们采用MCMC算法采用贝叶斯估计参数估计方法。然后使用一些密集的模拟研究评估该方法。最后,拟议的模型已经应用于分析伊朗劳动力调查的数据集。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号