Original title: Překážkové modely v neživotním pojištění
Translated title: Hurdle models in non-life insurance
Authors: Tian, Cheng ; Pešta, Michal (advisor) ; Branda, Martin (referee)
Document type: Master’s theses
Year: 2018
Language: eng
Abstract: A number of articles only present hurdle models for count data. we are motivated to present hurdle models for semi-continuous data. Because semi- continuous data is also commonly seen in non-life insurance. The thesis deals with the parameterization of various hurdle models for semi-continuous data besides for count data in non-life insurance. Two components of a hurdle model are modeled separately. A hurdle component is modeled by a logistic regression. For a semi-continuous data, a continuous component is modeled by several various regressions. Parameters of each component are estimated through maximum likelihood estimation. Model selection is mentioned before theoretical approaches are applied on the vehicle insurance data. Finally, we get some predicted values based on the fitted models. The prediction gives insurance companies a general idea on setting premium but not accurate. 1
Keywords: hurdle model; logistic regression; non-life insurance; semi-continuous data; logistická regrese; neživotní pojištění; překážkový model; semikontinuální data

Institution: Charles University Faculties (theses) (web)
Document availability information: Available in the Charles University Digital Repository.
Original record: http://hdl.handle.net/20.500.11956/94848

Permalink: http://www.nusl.cz/ntk/nusl-372991


The record appears in these collections:
Universities and colleges > Public universities > Charles University > Charles University Faculties (theses)
Academic theses (ETDs) > Master’s theses