In this paper, we study the two-parameter maximum likelihood estimation （MLE）problem for the GE distribution with consideration of interval data. In the presence of interval data, the analytical forms for the restri...In this paper, we study the two-parameter maximum likelihood estimation （MLE）problem for the GE distribution with consideration of interval data. In the presence of interval data, the analytical forms for the restricted MLE of the parameters of GE distribution do not exist. Since interval data is kind of incomplete data, the EM algorithm can be applied to compute the MLEs of the parameters. However the EM algorithm could be less effective.To improve effectiveness, an equivalent lifetime method is employed. The two methods are discussed via simulation studies.展开更多
基金Supported by the Natural Science Foundation of Guangdong Province (Grant No. S2012040007369)the Distinguished Young Talents in Higher Education of Guangdong (Grant No. 2012LYM 0089)the National Natural Science Foundation of China (Grant No. 71171103)
文摘In this paper, we study the two-parameter maximum likelihood estimation （MLE）problem for the GE distribution with consideration of interval data. In the presence of interval data, the analytical forms for the restricted MLE of the parameters of GE distribution do not exist. Since interval data is kind of incomplete data, the EM algorithm can be applied to compute the MLEs of the parameters. However the EM algorithm could be less effective.To improve effectiveness, an equivalent lifetime method is employed. The two methods are discussed via simulation studies.
