【摘 要】
：
Bias and variance depend on a particular parameterization.The Maximum Likelihood Estimator (MLE).however, is parameter-invariant.So bias and variance are not satisfactory for the MLE and any other par
【机 构】
：
East Carolina University Greenville, NC 27834, U.S.A.
【出 处】
：
The Third IMS-China International Conference on Statistics a
论文部分内容阅读
Bias and variance depend on a particular parameterization.The Maximum Likelihood Estimator (MLE).however, is parameter-invariant.So bias and variance are not satisfactory for the MLE and any other parameter-invariant estimators.We provide analogues of bias and variance that are parameter-free.For this purpose,we require our estimators to be parameter-free and utilize the Kullback-Leibler (KL) risk.
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