基于正态尺度混合因子模型的稳健贝叶斯分析及其应用

Robust Bayesian Analysis and its Applications for Factor Analytic Model with Normal Scale Mixing

  • 摘要: 为了消除分布的偏移和异常点对统计推断的影响, 本文基于正态尺度混合, 对一般的因子分析模型展开稳健贝叶斯分析. Gibbs抽样器被用来从后验分布产生随机样本, 统计推断基于后验经验分布展开. 实际数据表明方法是有效的.

     

    Abstract: To down-weight the influence of the distributional deviations and outliers, in this paper, we carry out robust Bayesian analysis for general factor analytic model combined with normal scale mixture model. Gibbs sampler is used to draw random observations from the posterior. Statistical inferences are carried out based on the empirical distribution of these observations. Two real data sets are analyzed to illustrate the effectiveness of the proposed method.

     

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