Estimating the Claim Serverity Distribution using Variable Neighborhood Search

Authors

ศ.ดร.สำรวม จงเจริญ, น.ส.Kunjira Kingphai

Published

American Journal of Applied Sciences

Abstract

In this study, Variable Neighborhood Search (VNS) is utilized to estimate the parameters of actual motor insurance claims data set and compared them obtained by the Moment Estimation Methods (MOM) and Maximum likelihood Estimation Method (MLE) which are known as a conscientious method. Then, the Kolmogorov-Smirnov test (KS) is used to show how well the selected distribution fits the actual claims. From the results, we found that the lognormal distribution which their parameters were estimated from VNS technique fits the actual motor claims data set better than the other two techniques with significant level 0.01.

(2559). Estimating the Claim Serverity Distribution using Variable Neighborhood Search. American Journal of Applied Sciences, 13(–), 1400-1406.