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对称分布的非参数估计AI 解读

Substantial improvements in the accuracy of nonparametric estimates are achieved when the centre of a symmetric distribution is known. Resultant benefits for confidence bands for the distribution function are extended to confidence intervals for quantiles and also tolerance limits. When the symmetry centre is not known and must be estimated from the sample improvements in accuracy are still possible.

非参数贝叶斯区间估计AI 解读

Bayesian confidence bands for a distribution function are converted into confidence intervals for specified population quantilea and also for the mean. Bayesian tolerance limits are similarly constructed.