Parameter estimation for the bivariate Lomax distribution based on censored samples

In this paper, we estimate the parameters of the bivariate Lomax distribution of Marshall-Olkin bsed on right censored sample. The advantage of using the EM algorithm is that the observed data vector is viewed as being incomplete but regarded as an observable function of complete data. Then the EM algorithm exploits the reduced complexity of maximum likelihood estimation for complete data. We also derive the standard deviations of the estimates for this bivariate Lomax distribution. A simulation study is conducted to compare the estimated values with the true values.