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广义刀切法：有限样本与子样本规模AI 解读

This paper is concerned with bias-reduction properties of that generalized jackknife which pertains to a single-estimator, single-sample situation. Jackknifing is a technique for reducing bias by exploiting the dependence of the bias on sample size. In practice, this is carried out by reestimating the unknown parameter(s) with only part of the sample and combining the new and original estimates suitably weighted to produce cancellation in their biases. The size of the…

广义 Jackknife：有限样本与子样本大小AI 解读

This paper is concerned with bias-reduction properties of that generalized jackknife which pertains to a single-estimator, single-sample situation. Jackknifing is a technique for reducing bias by exploiting the dependence of the bias on sample size. In practice, this is carried out by reestimating the unknown parameter(s) with only part of the sample and combining the new and original estimates suitably weighted to produce cancellation in their biases. The size of the…