左截断右删失数据下OLLGG分布的参数估计

Parameter estimation of the Odd Log-Logistic Generalized Gompertz distribution under left-truncated and right-censored data

为了探索Odd Log-Logistic Generalized Gompertz(OLLGG)分布在生物学、社会学、计算机和市场营销等领域的广泛应用,本文研究左截断右删失数据下OLLGG分布的多参数回归模型,利用极大似然思想对参数进行估计。通过数值模拟,检验估计方法的有效性,并使用赤池信息量准则来选择适合的分布形式。最后,将本文的回归模型应用于channing house数据集,展示其良好的拟合效果。

In order to explore the widespread applications of Odd Log-Logistic Generalized Gompertz(OLLGG)distribution in fields such as biology,sociology,computer science and marketing,this paper studies a multi-parameter regression model for OLLGG distribution under left-truncated and right-censored data,and estimates the parameters using maximum likelihood thinking.Through numerical simulation,the effectiveness of the estimation method is verified,and the Akaike information criterion is used to select the appropriate distribution form.Finally,the regression model proposed in this article is applied to the channing house dataset to demonstrate its good fitting performance.