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Brief communication "Improving the actual coverage of subsampling confidence intervals in atmospheric time series analysis"

机译:简短交流“在大气时间序列分析中改善次采样置信区间的实际覆盖范围”

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In atmospheric time series analysis, where only one record is typically available, subsampling (which works under the weakest assumptions among resampling methods), is especially useful. In particular, it yields large-sample confidence intervals of iasymptotically/i correct coverage probability. Atmospheric records, however, are often not long enough, causing a substandard coverage of subsampling confidence intervals. In the paper, the subsampling methodology is extended to become more applicable in such practically important cases.
机译:在通常只有一条记录可用的大气时间序列分析中,子采样(在重新采样方法中最弱的假设下有效)特别有用。特别是,它会产生渐近正确覆盖率的大样本置信区间。但是,大气记录通常不够长,导致对次采样置信区间的覆盖不合标准。在本文中,扩展了子采样方法,使其在此类实际重要的情况下更加适用。

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