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Stabilizing the asymptotic covariance of an estimate

机译:稳定估计的渐近协方差

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Suppose as n → ∞ for some estimate of θ in R p . If p =1 and g ( θ )= ∫ 0 θ V ( x ) ? 1/2 dx , it is well known that as n → ∞ , the distribution often being less skew so that inference based on the approximation should be more accurate than inference based on the approximation . If p > 1 there is generally no such one to one transformation g ( ? ). We consider three different types of stabilization of V ( θ ). We also consider the problem of finding g ( ? ) so that the components of are asymptotically independent.
机译:对于R p 中的θ的某些估计,假设n→∞。如果p = 1且g(θ)=∫ 0 θ V(x)? 1/2 dx,众所周知,当n→∞时,分布通常偏斜较小,因此基于近似的推理应比基于近似的推理更准确。如果p> 1,通常不存在这样的一对一转换g(?)。我们考虑三种不同类型的V(θ)稳定。我们还考虑了找到g(?)的问题,使得g的分量渐近独立。

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