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Classical sampling theory considers a finite population, \(U = \left \{ {1, \ldots ,N} \right \},\) of known size, N, with a vector of fixed unknown values of a variable of interest, y = ( y 1, …, y N ). A sample of size n, \(s=\left \{ {{s_{{i_1}}}, \ldots ,{s_{{i_n}}}} \right \},\) is selected by a sample design, which assigns to each possible sub-set of U a known probability— p( s).

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Superpopulation Models in Survey Sampling

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  • 发表日期：

    2025年

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  • Gad Nathan

摘要

Classical sampling theory considers a finite population, \(U = \left \{ {1, \ldots ,N} \right \},\) of known size, N, with a vector of fixed unknown values of a variable of interest, y = ( y 1, …, y N ). A sample of size n, \(s=\left \{ {{s_{{i_1}}}, \ldots ,{s_{{i_n}}}} \right \},\) is selected by a sample design, which assigns to each possible sub-set of U a known probability— p( s).