Truncated Lomax Distribution with Applications in Insurance
A new distribution with two extra parameters named a truncated Lomax distribution is proposed which is more flexible than many well-known heavy tailed distributions. We present some of its mathematical properties including ordinary moments, quantile function, and order statistics. The method of maximum likelihood to estimate the model parameters is discussed and the behavior of maximum likelihood estimator is studied. The importance of the new distribution is illustrated by means of the two real data sets and the capability in modeling of insurance data is evaluated. The results indicate that the new distribution can provide better fits than exponential, weibull, gamma, lomax, lognormal, log-logistic, and generalized extreme value distributions in insurance. Therefore, the truncated Lomax distribution can be an alternative for modeling the catastrophe loss in insurance applications.
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