A Bayesian Approach to Weibull Distribution with Application to Insurance Claims Data

Statistical distributions are of great interest for actuaries in modelling and fitting the distribution various data sets. It can be used to present a description risk exposure on investment, where level determined by “key indicators” that usually functions statistical model. Financial mathematicians actuarial scientists often use such key indicators determine degree which particular company is subject certain aspects risk, arise from changes underlying variables as prices equity, rates fluctuations, or exchange rates. Weibull one most popular models employed financial management problems behaviours lifetime event forecast stock pricing movement uncertainly prediction. In this study, Bayesian approach model assumption gamma prior parameters has been proposed. A computational study based measures conducted, proving proposed claim amount. Along line, assessing performance method, results simulations have conducted explore efficiency estimators compared maximum likelihood (MLE) simulated annealing algorithm (SA). Finally, an real set analyzed, effectively insurance data.