Abstract
Statisticians are always interested in how to use sample?statistics?to estimate population?parameters. Both maximum likelihood estimation?(MLE) and?method of moments?(MOM) are the most popularly used in the statistical field, but they each have their own drawbacks. For instance, these two methods cannot be applied to parameter estimation of the Cauchy distribution. This paper propose a geometric approach to estimation that is based on the concept of the minimum distance. It can be used to estimate not only the distribution parameters with complete and censored data but also parameters in Cox’s proportional hazards model. Computer simulation results show that the new method has a great improvement in variance and mean squared error on the traditional methods.