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摘要暂缺

摘要暂缺

库存成本估计中的模型分层AI 解读

This article describes a method for developing an efficiently stratified sampling design for a generalized difference estimator, using a superpopulation model. The effectiveness of model-based stratification is compared to several conventional designs, using a data base from a complete audit of an inventory of 8,069 items. In this application, model-based designs reduce the required sample size from 9% to 40%, compared to the conventional designs.

利用多变量辅助信息的有限总体抽样AI 解读

This article examines strategies that are approximately design-unbiased and nearly optimal, assuming a large-sample survey and a regression superpopulation model. A new class of predictors is proposed to link certain features of optimal design-unbiased and model-unbiased predictors. Generalized regression predictors are shown to pervade the subclass of asymptotically design-unbiased (ADU) predictors. Generalized regression predictors are combined with model-based…

衡量统计成本分摊的精度AI 解读

This article examines the use of regression analysis for allocating indirect costs. When multiple regression is used to estimate the weights of several allocation factors, conventional standard errors and correlation coefficients can be misleading with respect to the statistical precision of the cost allocations. This article develops alternative allocation approaches and measures of precision that use linear prediction theory and Bayesian inference. The proposed methods are…