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基于链接数据的小区域估计AI 解读

Abstract Data linkage can be used to combine values of the variable of interest from a national survey with values of auxiliary variables obtained from another source, such as a population register, for use in small area estimation. However, linkage errors can induce bias when fitting regression models; moreover, they can create non-representative outliers in the linked data in addition to the presence of potential representative outliers. In this paper, we adopt a secondary…

含不可忽略无应答的调查数据对数线性模型AI 解读

SUMMARY We demonstrate the feasibility of constructing, interpreting and fitting computable log-linear models to categorical survey data with arbitrary non-nested patterns of non-ignorable non-response. Under our approach, the non-response probability for each cell of the classification defined by the categories of interest is modelled separately from the classification probability itself, and we adopt a model formulation which allows the non-response model to depend on…

有限总体分布函数估计量的性质AI 解读

Two leading estimators of the finite population distribution function are studied. Their large-sample mean squared errors are compared, under a given model. Neither estimator is universally better; circumstances are identified where the model-based estimator would do poorly, despite employing the correct model.

有限总体分布函数估计量的性质AI 解读

Two leading estimators of the finite population distribution function are studied. Their large-sample mean squared errors are compared, under a given model. Neither estimator is universally better; circumstances are identified where the model-based estimator would do poorly, despite employing the correct model.

利用调查数据估计分布函数AI 解读

A simple method for estimating population distribution functions and associated quantiles from sample survey data is described and some asymptotic theory for it presented. The method assumes a model-based approach to survey estimation and allows auxiliary population information to be directly incorporated into the estimation process. Monte Carlo results comparing the proposed method with conventional design-based methods are given. These suggest that the model-based approach…

利用调查数据估计分布函数AI 解读

A simple method for estimating population distribution functions and associated quantiles from sample survey data is described and some asymptotic theory for it presented. The method assumes a model-based approach to survey estimation and allows auxiliary population information to be directly incorporated into the estimation process. Monte Carlo results comparing the proposed method with conventional design-based methods are given. These suggest that the model-based approach…

线性回归中斜率的估计与异常值识别AI 解读

The paper presents a large sample method for estimating the slope parameter in a linear model by minimizing a loss function related to the empirical cumulant generating function of the error distribution. A family of estimators, indexed by a real parameter, is obtained and consistency and asymptotic normality established. The optimum member of the family is that which has minimum variance with respect to the parameter. This minimization together with a characterization…

线性回归中的斜率估计与异常值识别AI 解读

The paper presents a large sample method for estimating the slope parameter in a linear model by minimizing a loss function related to the empirical cumulant generating function of the error distribution. A family of estimators, indexed by a real parameter, is obtained and consistency and asymptotic normality established. The optimum member of the family is that which has minimum variance with respect to the parameter. This minimization together with a characterization…