论文标题
在长度偏见的Birnbaum-Saunders回归模型上，应用于气象数据
On a length-biased Birnbaum-Saunders regression model applied to meteorological data
论文作者
论文摘要
长度偏见的Birnbaum-Saunders分布对环境科学既有用，也是实用的。在本文中，我们最初为长度偏见的birnbaum-saunders分布得出了一些新属性，表明其参数之一是模式，并且是双峰的。然后，我们基于此分布引入了一个新的回归模型。我们实施使用最大似然方法来估计参数估计，方法间隔估计并考虑三种类型的残差。进行了一项精致的蒙特卡洛研究，以评估基于似然估计的性能，置信区间和残差的经验分布。最后，我们通过使用真实的气象数据集说明了提出的回归模型。
The length-biased Birnbaum-Saunders distribution is both useful and practical for environmental sciences. In this paper, we initially derive some new properties for the length-biased Birnbaum-Saunders distribution, showing that one of its parameters is the mode and that it is bimodal. We then introduce a new regression model based on this distribution. We implement use the maximum likelihood method for parameter estimation, approach interval estimation and consider three types of residuals. An elaborate Monte Carlo study is carried out for evaluating the performance of the likelihood-based estimates, the confidence intervals and the empirical distribution of the residuals. Finally, we illustrate the proposed regression model with the use of a real meteorological data set.
