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首页> 外文期刊>Sequential analysis >Two-stage estimation for a normal mean having a known lower bound of variance with final sample size defined via Gini's mean difference and mean absolute deviation
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Two-stage estimation for a normal mean having a known lower bound of variance with final sample size defined via Gini's mean difference and mean absolute deviation

机译：通过吉尼的均值差和均值绝对偏差定义的具有已知方差下界的最终均值的法均值的两阶段估计

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摘要

Revisiting Stein (1945, 1949) as well as Mukhopadhyay and Duggan (1997), we have proposed new two-stage procedures under both minimum risk point estimation and fixed-width confidence interval configurations for a normal mean mu when a lower bound of variance is known to us. New unbiased estimators based on sample standard deviation, Gini's mean difference (GMD), and mean absolute deviance (MAD) are constructed to define the final sample sizes. The new procedures enjoy both asymptotic first-order and second-order properties, followed by simulated performances. Real data illustrations of the marigold data are also included.
机译：回顾Stein（1945，1949）以及Mukhopadhyay和Duggan（1997），我们提出了在最小风险点估计和固定宽度置信区间配置下，当方差下限为我们知道的。构建了基于样本标准偏差，吉尼平均差（GMD）和平均绝对偏差（MAD）的新无偏估计量，以定义最终样本量。新过程既具有渐近的一阶和二阶性质，又具有模拟性能。万寿菊数据的真实数据插图也包括在内。

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