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    188宝金博页面版: An adaptive algorithm for estimating inclusion probabilities …

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    内容提示： An adaptive algorithm for estimating inclusion probabilities and performing Horvitz-Thompson criterion in complex designs Lorenzo Fattorini Dipartimento di Metodi Quantitativi, Università di Siena, P.za S. Francesco 8, 53100 Siena, Italy Abstract An algorithm for estimating inclusion probabilities and applying the Horvitz-Thompson criterion is considered for complex sampling designs, when the computation of the actual inclusion probabilities is prohibitive. The inclusion probabilities are estimated by ...

    文档格式：PDF | 页数：32 | 浏览次数：4 | 上传日期：2015-12-31 23:28:25 | 文档星级：
    An adaptive algorithm for estimating inclusion probabilities and performing Horvitz-Thompson criterion in complex designs Lorenzo Fattorini Dipartimento di Metodi Quantitativi, Università di Siena, P.za S. Francesco 8, 53100 Siena, Italy Abstract An algorithm for estimating inclusion probabilities and applying the Horvitz-Thompson criterion is considered for complex sampling designs, when the computation of the actual inclusion probabilities is prohibitive. The inclusion probabilities are estimated by means of independent replications of the sampling scheme. In turn, the number of replications is determined on the basis of the stability of the resulting estimates as well as on the basis of their precision, checked by means of the Bennet inequality. The number of replications is adaptively increased until a suitable level of precision is reached in a sustainable computational time. Details on the FORTRAN routines adopted for implementing the algorithm are given. The procedure is checked using three artificial examples. Keywords: Complex sampling schemes; Horvitz-Thomson estimation; Replications; Empirical inclusion probabilities; Bennet inequality.

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