Estimation of Reliability Function for Inverse Gaussian Distribution Model with Application by Using Monte Carlo Simulation

In this work we consider the Inverse Gaussian distribution model of two parameters, because it have many applications in the fields of statistics and reliability. Mathematical and statistical properties of the distribution are given together with illustration. Moments and higher moments of the distribution properties and of the reliability and hazard functions are discussed theoretically. Two methods of estimation namely moments method and maximum likelihood method are used to estimate the distribution parameters. The obtained estimators are utilized together with Basu method to estimate the reliability and the
hazard function.These methods are discussed theoretically and applied practically by using three procedures of generating random sample from the distribution. Bias measure is used to compare between these procedures.The computer programs are coding in appendices by the run is made by using “MathCAD 14”.