大理大学学报 ›› 2025, Vol. 10 ›› Issue (12): 1-5.

• 数学与计算机科学 •    下一篇

广义逆高斯分布的参数估计方法研究

  

  1. 昭通学院数学与统计学院,云南昭通 657000
  • 出版日期:2025-12-15 发布日期:2026-01-16
  • 基金资助:
    云南省地方本科高校基础研究联合专项资金项目(202301BA070001-095;202301BA070001-092);云南省中青年学
    术和技术带头人后备人才项目(202405AC350086);昭通学院校级一流本科课程建设项目(Ztujk202535)

Research on Parameter Estimation Methods for the Generalized Inverse Gaussian Distribution

  1. School of Mathematics and Statistics, Zhaotong University, Zhaotong, Yunnan 657000, China
  • Online:2025-12-15 Published:2026-01-16

摘要: 针对广义逆高斯分布的参数估计问题,提出一种间接极大似然估计方法。针对阶数参数λ < 0的情形,通过对广义逆高斯分布的参数进行变量替换,并引入一个服从均匀分布U (0,1)的协变量,将替换后的待估参数假设为关于协变量的参数函数。进一步地,对该函数中的参数进行极大似然估计,从而估计出广义逆高斯分布中的参数,并通过实际案例验证了所提方法的有效性和实用性。

关键词: 广义逆高斯分布, 极大似然估计, 变量替换, 协变量

Abstract: An indirect maximum likelihood estimation method is proposed for the parameter estimation of the generalized inverse
Gaussian distribution. For the case where the order parameter λ < 0, variable substitution is performed on the parameters of the generalized inverse Gaussian distribution, and a covariate following the uniform distribution U(0, 1) is introduced. The substituted parameters to be estimated are then assumed to be a parametric function of this covariate. Furthermore, maximum likelihood estimation is applied to the parameters within this function to estimate the parameters of the generalized inverse Gaussian distribution. The effectiveness and practicality of the proposed method are validated through real-world case studies.

Key words: generalized inverse Gaussian distribution, maximum likelihood estimation, variable substitution, covariates

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