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arXiv · 2206.01355

Traffic Count Data Analysis Using Mixtures of Kato--Jones Distributions

Kota Nagasaki·Shogo Kato·Wataru Nakanishi·M. C. Jones
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Abstract

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.

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Kota Nagasaki, Shogo Kato, Wataru Nakanishi, M. C. Jones. 2022-06-03. Traffic Count Data Analysis Using Mixtures of Kato--Jones Distributions. https://arxiv.org/abs/2206.01355

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