Truncated Gamma-Truncated Lomax Distribution in Modelling Data Claims
Abstract
One of the methods to analyze the risk of loss on insurance companies based on the historical data on claim payments is modelling the data into severity distribution. This research deals with severity distribution by connecting two distribution Truncated Gamma and Truncated Lomax in modelling claim payments. The Kolmogorov-Smirnov test is used to test the fit of model. The result shows that Truncated Gamma-Truncated Lomax distribution is the best model to analyze the risk of loss based on data claim payments. The AIC value of 1533,915 and the BIC value of 1550,132.
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DOI: http://dx.doi.org/10.12962/j24775401.v10i2.21948
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International Journal of Computing Science and Applied Mathematics by Pusat Publikasi Ilmiah LPPM, Institut Teknologi Sepuluh Nopember is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at https://iptek.its.ac.id/index.php/ijcsam.