The Survival Model Based On Bivariate Copula And Its Parameter Estimation Based On Censored Data

Dependent data have wide applications and are important in survival analysis, when we deal with dependent data, usually it’s hard for us to get complete data, we can only get the data with a censored structure. Similarly, censored data have important applications in survival analysis, mathematical statistics and other fields.When dealing with dependent data, the Copula function is always one of the most important ways to use. In this paper, we hope to use the Copula function to describe the correlation be-tween the two variables, with Pareto distribution to be the marginal distribution of the variables, and construct the survival analysis model, then we estimate the parameters of the model with censored dependent data, we use numerical simulation to verify the quality of the estimation. At last, we use our model to analyze a data set from the DRS group, and compare the result of our model with those obtained from other models.