dc.contributor.author | Laha, Arnab Kumar | |
dc.contributor.author | A. C., Pravida Raja | |
dc.contributor.author | Ghosh, Dilip Kumar | |
dc.date.accessioned | 2019-05-23T20:44:46Z | |
dc.date.available | 2019-05-23T20:44:46Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Laha, A.K., Raja, P., & Ghosh, D.K. (2017). Distribution of Traffic Accident Times in India - Some Insights using Circular Data Analysis . International Journal of Business Analytics and Intelligence , 5(1), 26-35. | en_US |
dc.identifier.uri | http://hdl.handle.net/11718/21911 | |
dc.description.abstract | Traffic accidents are a major hazard for travellers on
Indian roads. These are caused by a variety of reasons
including the bad condition of roads, traffic density, lack
of proper training of drivers, slack in enforcement of traffic
rules, poor road lighting etc. It is further known that certain
times of the day are more prone to traffic accidents than
others. In this paper we investigate the distribution of
traffic accident times using the data published annually
by the National Crime Records Bureau (NCRB) over
the period 2001-2014 using the tools of circular data
analysis. It is seen that the observed distribution of the
traffic accident times in most years is bimodal. Thus,
several modelling strategies for bimodal distributions
are tried which include fitting of mixture of von-Mises
distributions and mixture of Kato-Jones distribution. It is
seen from this analysis that the distribution of the traffic
accident times are changing over the years. Notably,
the proportion of accidents happening in late night has
reduced over the years while the same has increased
for late evening hours. Some more insights obtained
from this analysis are also discussed. | en_US |
dc.subject | Circular Statistics | en_US |
dc.subject | Kato-Jones Distribution | en_US |
dc.subject | Mixture Distribution | en_US |
dc.title | Distribution of traffic accident times in India - some insights using circular data analysis | en_US |
dc.title.alternative | International Journal of Business Analytics and Intelligence | en_US |
dc.type | Article | en_US |