Research Article Open Access

Estimating the Claim Severity Distribution using Variable Neighborhood Search

Kunjira Kingphai1 and Samruam Chongcharoen1
  • 1 Graduate School of Applied Statistic, National Institute of Development Administration, Bangkok, Thailand


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 (K-S) 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.

American Journal of Applied Sciences
Volume 13 No. 12, 2016, 1400-1406


Submitted On: 22 December 2015 Published On: 19 December 2016

How to Cite: Kingphai, K. & Chongcharoen, S. (2016). Estimating the Claim Severity Distribution using Variable Neighborhood Search. American Journal of Applied Sciences, 13(12), 1400-1406.

  • 1 Citations



  • Variable Neighborhood Search (VNS)
  • Claim Severity Distribution
  • Maximum Likelihood Estimation Method (MLE)
  • Moment Estimation Method (MOM)