论文标题
使用Kato的混合物 - 琼斯分布的交通计数数据分析
Traffic Count Data Analysis Using Mixtures of Kato--Jones Distributions
论文作者
论文摘要
我们讨论了交通计数数据的建模，该数据显示了一天内交通量的变化。对于建模，我们采用了Kato-Jones分布的混合物，其中每个组件都是单峰的，并且提供了各种偏度和峰度。我们考虑了参数估计的两种方法，即一种修改的矩和最大似然方法。这些方法被认为可用于将所提出的混合物拟合到我们的数据中。结果，交通量的变化分为早晨和晚上的交通，其分布的形状不同，尤其是不同程度的偏度和峰度。
We discuss the modelling of traffic count data that show the variation of traffic volume within a day. For the modelling, we apply mixtures of Kato-Jones distributions in which each component is unimodal and affords a wide range of skewness and kurtosis. We consider two methods for parameter estimation, namely, a modified method of moments and the maximum likelihood method. These methods were seen to be useful for fitting the proposed mixtures to our data. As a result, the variation in traffic volume was classified into the morning and evening traffic whose distributions have different shapes, particularly different degrees of skewness and kurtosis.
