Bayesova metoda u neživotnom osiguranju

Kegel, Katja (2014) Bayesova metoda u neživotnom osiguranju. Diploma thesis, Faculty of Science > Department of Mathematics.

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Through this dissertation, we have shown how one can use Bayesian statistics and Markov Chain Monte Carlo techniques in outstanding liabilities of an insurance company. We met with the basic concepts of Bayesian statistics and the most important term known as the Bayes' theorem. In addition, we introduced the properties of Markov chain techniques and Markov chain Monte Carlo including the two algorithms also known as Metropolis-Hastings algorithm and Gibbs sampling. Based on the given data, we observed and analyzed the two models, lognormal and exponential, and have been able to select the one fitting the data better. To select a better model, we used graphical analysis and deviance criterion (DIC) and lognormal model was selected as the one that fits the data better. Finally, using MCMC methods we assessed future claim amounts that must be paid, as well as missing values, and once again we confirmed that the selected lognormal model gave us quite satisfactory results.

Item Type: Thesis (Diploma thesis)
Supervisor: Slijepčević, Siniša
Date: 2014
Number of Pages: 53
Subjects: NATURAL SCIENCES > Mathematics
Divisions: Faculty of Science > Department of Mathematics
Depositing User: Iva Prah
Date Deposited: 03 Jun 2015 09:38
Last Modified: 03 Jun 2015 09:38

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