中文摘要：

偏t正态分布是分析尖峰，厚尾数据的重要统计工具之一。研究提出了偏t正态数据下混合线性联合位置与尺度模型，通过EM算法和Newton-Raphson方法研究了该模型参数的极大似然估计。并通过随机模拟试验验证了所提出方法的有效性。最后，结合实际数据验证了该模型和方法具有实用性和可行性。

英文摘要：

Skew-t-normal distribution is one of the most important statistical tools to analyze the obvious peak and fat tail data. A linear mixture joint location and scale model with skew-t-normal data is proposed in this paper. The maximum likelihood estimation of the unknown parameters of this model is investigated based on Expectation Maximization （EM） algorithm and Newton-Raphson method. Furthermore, the proposed procedure works satisfactorily through Monte Carlo experiments. Finally, a real example shows that both this model and method are useful and effective.