Modelling the Number of Road Accidents - Procházka, Jiří; Flimmel, Samuel; Čamaj, Matej; Bašta, Milan (Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu, 2017)
Modelling the number of daily road accidents can be beneficial not only for insurance companies but also for other institutions such as the national road administration, national insurers’ bureau etc. Accurate predictions of the number of road accidents could be beneficial in terms of efficient liquidation planning, improving the reserving processes, streamlining the capital allocation and road maintaining. Consequently, it is relevant to build a viable model for predicting the number of daily road accidents. One of the most important parts of the model is the model of daily seasonality. Since this seasonality exhibits a long seasonal period, approaches based on basis expansion can be used for its modelling. We also investigate the multiple seasonality pattern and specific time events which could potentially affect the number of accidents. Furthermore, the impact of different external variables, such as the average daily temperature, rainfall and other factors influencing human driving skills, will also be investigated
20-th AMSE. Applications of Mathematics and Statistics in Economics. International Scientific Conference: Szklarska Poręba, 30 August- 3 September 2017. Conference Proceedings Full Text Papers, s. 355-364
Keywords: road accidents; long seasonality modeling; multiple seasonality