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首页> 外文期刊>Bernoulli: official journal of the Bernoulli Society for Mathematical Statistics and Probability >Normal approximation and smoothness for sums of means of lattice-valued random variables
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Normal approximation and smoothness for sums of means of lattice-valued random variables

机译:晶格值随机变量的平均值之和的正态逼近和平滑度

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摘要

Motivated by a problem arising when analysing data from quarantine searches, we explore properties of distributions of sums of independent means of independent lattice-valued random variables. The aim is to determine the extent to which approximations to those sums require continuity corrections. We show that, in cases where there are only two different means, the main effects of distribution smoothness can be understood in terms of the ratio ρ _(12) = (e2n_1)/(e1n_2), where e1 and e2 are the respective maximal lattice edge widths of the two populations, and n_1 and n_2 are the respective sample sizes used to compute the means. If ρ_(12) converges to an irrational number, or converges sufficiently slowly to a rational number; and in a number of other cases too, for example those where ρ _(12) does not converge; the effects of the discontinuity of lattice distributions are of smaller order than the effects of skewness. However, in other instances, for example where ρ _(12) converges relatively quickly to a rational number, the effects of discontinuity and skewness are of the same size. We also treat higher-order properties, arguing that cases where ρ _(12) converges to an algebraic irrational number can be less prone to suffer the effects of discontinuity than cases where the limiting irrational is transcendental. These results are extended to the case of three or more different means, and also to problems where distributions are estimated using the bootstrap. The results have practical interpretation in terms of the accuracy of inference for, among other quantities, the sum or difference of binomial proportions.
机译:受分析隔离检疫数据时出现的问题的启发,我们探索了独立晶格值随机变量的独立均值之和的分布特性。目的是确定对这些和的近似值需要进行连续性校正的程度。我们表明,在只有两种不同方式的情况下,可以通过比率ρ_(12)=(e2n_​​1)/(e1n_2)来理解分布平滑度的主要影响,其中e1和e2分别是最大值两个总体的晶格边缘宽度,n_1和n_2是用于计算均值的各自样本大小。如果ρ_(12)收敛到一个无理数,或足够缓慢地收敛到一个有理数;在许多其他情况下,例如ρ_(12)不收敛的情况;晶格分布不连续的影响要比偏斜的影响要小。但是,在其他情况下,例如ρ_(12)相对较快地收敛到一个有理数,则不连续性和偏度的影响大小相同。我们还处理高阶性质,认为ρ_(12)收敛到代数无理数的情况比有限无理数是先验的情况更不容易受到不连续性的影响。这些结果扩展到三个或更多不同均值的情况,还扩展到使用引导程序估计分布的问题。该结果在推断二项式比例之和或差异的准确性方面具有实际意义。

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