We propose the finite mixture of skewed sub-Gaussian stable distributions. The maximum likelihood estimator for the parameters of proposed finite mixture model is computed through the expectation-maximization algorithm. The proposed model contains the finite mixture of normal and skewed normal distributions. Since the tails of proposed model is heavier than even the Student's t distribution, it can be used as a powerful model for robust model-based clustering. Performance of the proposed model is demonstrated by clustering simulation data and two sets of real data.
翻译:我们提出偏斜的亚高加索稳定分布的有限混合物。 提议的有限混合物模型参数的最大可能性估计值是通过预期最大化算法计算的。 提议的模型包含正常和偏斜正常分布的有限混合物。 由于提议的模型的尾部比学生的T分布还要重, 可以用它作为强大的基于模型的强大组合模型。 拟议的模型的性能表现通过集成模拟数据和两套真实数据来证明。