Traffic count data analysis using mixtures of Kato–Jones distributions Article Swipe
Kota NAGASAKI
,
Shogo Kato
,
Wataru Nakanishi
,
M. C. Jones
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/jrsssc/qlae057
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1093/jrsssc/qlae057
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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- https://doi.org/10.1093/jrsssc/qlae057
- OA Status
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- References
- 27
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- OpenAlex ID
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https://doi.org/10.1093/jrsssc/qlae057Digital Object Identifier
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Traffic count data analysis using mixtures of Kato–Jones distributionsWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-10-28Full publication date if available
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Kota NAGASAKI, Shogo Kato, Wataru Nakanishi, M. C. JonesList of authors in order
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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Statistics, Count data, Mathematics, Environmental science, Computer science, Poisson distributionTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| corresponding_author_ids | https://openalex.org/A5040397585 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I4400009020 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.20546671 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |