Approximations for Densities of Sufficient Estimators
Approximations for Densities of Sufficient Estimators
复制标题
足够估计量的密度近似
DOI：
10.1007/978-3-642-04898-2_119
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
J. Abril
中科院分区：
文献类型：
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作者：
J. Abril
Durbin （1980a）提出了一种获得充分估计量密度渐近展开式的简单方法。这个展开式是一个级数它的幂是n-1，其中n是样本量，而埃奇沃斯展开式的幂是n-1/2。基本的近似就是这个级数的第一项。它的误差为n-1阶与通常的渐近正态近似的误差为n-1/2相比。通过重整化，误差的数量级通常可以降低到n-3/2阶。
Durbin (1980a) proposed a simple method for obtaining asymptotic expansions for the densities of sufficient estimators. The expansion is a series which is effectively in powers of n-1, where n is the sample size, as compare with the Edgeworth expansion which is in powers of n-1/2. The basic approximation is just the first term of this series. This has an error of order n-1 compare to the error of n-1/2 in the usual asymptotic normal approximation. The order of magnitude of the error can generally be reduced to order n-3/2 by renormalization.