Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. ,  obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data.  construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions.  show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators.
['Guang Cheng', 'Lan Zhou', 'Xiaohong Chen', 'Jianhua Z. Huang']
I am writing a research paper on a idea Efficient estimation of semiparametric copula models for bivariate survival data
[{"from": "human", "value": "I am writing a research paper on a idea Efficient estimation of semiparametric copula models for bivariate survival data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. ,  obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data.  construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions.  show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators."}]