庄唯. 上截断几何混合分布估计方法研究[J]. 应用概率统计, 2021, 37(5): 495-506. DOI: 10.3969/j.issn.1001-4268.2021.05.005
引用本文: 庄唯. 上截断几何混合分布估计方法研究[J]. 应用概率统计, 2021, 37(5): 495-506. DOI: 10.3969/j.issn.1001-4268.2021.05.005
ZHUANG Wei. Research on Estimation Methods for the Upper-Truncated Geometric Mixture Distribution[J]. Chinese Journal of Applied Probability and Statistics, 2021, 37(5): 495-506. DOI: 10.3969/j.issn.1001-4268.2021.05.005
Citation: ZHUANG Wei. Research on Estimation Methods for the Upper-Truncated Geometric Mixture Distribution[J]. Chinese Journal of Applied Probability and Statistics, 2021, 37(5): 495-506. DOI: 10.3969/j.issn.1001-4268.2021.05.005

上截断几何混合分布估计方法研究

Research on Estimation Methods for the Upper-Truncated Geometric Mixture Distribution

  • 摘要: 几何模型是实际生活中被广泛应用的离散型概率模型,而上截断几何模型在实际生活中也有着重要的应用.本文将对上截断几何混合模型的参数及非参数方法进行系统阐述.利用高斯分布、贝塔分布和伽马分布提出了未知参数的最大条件似然估计,并结合数值模拟和实例说明上截断几何模型的应用.

     

    Abstract: Geometric model is a widely used discrete probabilistic model. The uppper-truncated geometric model which is derived from geometric model also has important applications in real life. In this paper we will specify the upper-truncated geometric mixed model, study its non-parametric and parameter estimation methods. The maximum conditional likelihood estimation of unknown parameters is proposed based on gaussian distribution, beta distribution and gamma distribution. Meanwhile, combined with simulation and an example, the applications of the upper-truncated geometric model is illustrated.

     

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