Détection d'outliers. Modélisation et prédiction. Application aux données de véhicules d'occasion.

Abstract : Autobiz publishes information on the automotive sector. The subject of this thesis is to give more tools for best understanding the used cars market by proposing modeling the price and the sale duration of vehicles. In our disposal we have a dataset consisted of used car advertisements automatically collected from the most popular website in France. Such data records often include outlying values. So, we need to start our analysis by considering outliers problem and we propose an outliers detector for univariate case for which we study asymptotic properties. Next, we develop a predicting model for used cars price. Although enumerable amount of works are stored in the literature we see that each of them lacks rigorous statistical foundations. We investigate the relationships between the price, the mileage, the age and others vehicle characteristics. More precisely we discuss how incorporate these variables in a model and compare different modeling approaches with the object to find the one best fitting the dataset and easy to implement. Expert’s opinions are minded at different stages of the model-building process. Next, we identify variables and how they affect the probability of a used vehicle's sale from a list of explanatory variables related to price, mileage and age. In the sequel, we build a model allowing predicting the sale duration. Finally, we discuss about modeling sales of used cars by using the negative binomial distribution.
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  • HAL Id : tel-01432630, version 1

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Solohaja Faniaha Dimby. Détection d'outliers. Modélisation et prédiction. Application aux données de véhicules d'occasion. . Statistiques [stat]. Université Paris 1 Panthéon-La Sorbonne, 2015. Français. ⟨tel-01432630⟩

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