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A Simple Method for the Construction of Empirical Confidence Limits for Economic Forecasts

构造经济预测经验置信限的简便方法

A simple method for the construction of empirical confidence intervals for time series forecasts is described. The procedure is to go through the series making a forecast from each point in time. The comparison of these forecasts with the known actual observations will yield an empirical distribution of forecasting errors. This distribution can then be used to set confidence intervals for subsequent forecasts. The technique appears to be particularly useful when the…

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Systematic Biases in Panel Surveys Due to Differential Nonresponse

差异性无回应导致的面板调查系统偏差

Panel surveys involve repeated observations made on the same sample of populalation units. In some of these studies systematic biases have appeared; specifically, if Ri is an estimate made from panels appearing in the sample for the i th time, then it has been observed that these estimates sometimes vary systematically with i. It is tempting to interpret these phenomena as being due to conditioning of the panel of respondents. In this article it is shown that these…

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Systematic Biases in Panel Surveys Due to Differential Nonresponse

差异性无应答导致的面板调查系统偏差

Panel surveys involve repeated observations made on the same sample of populalation units. In some of these studies systematic biases have appeared; specifically, if Ri is an estimate made from panels appearing in the sample for the i th time, then it has been observed that these estimates sometimes vary systematically with i. It is tempting to interpret these phenomena as being due to conditioning of the panel of respondents. In this article it is shown that these…

AI 解读阅读原文 ↗BibTeX ↓

Sample Selection and the Choice of Estimator in Two-Way Stratified Populations

双向分层总体中的样本选择与估计量选择

The paper studies the effect on variance of the method of sample selection and the choice of estimator in a two-way stratified population. Three methods of sampling, simple random and one and two-way stratified, are studied in conjunction with estimators which use no population information, one and two sets of marginal frequencies and cell frequencies. It is shown that whether the information in the population frequencies is used in the sample draw or in the estimator, the…

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Sample Selection and the Choice of Estimator in Two-Way Stratified Populations

双向分层总体中的抽样方式与估计量选择

The paper studies the effect on variance of the method of sample selection and the choice of estimator in a two-way stratified population. Three methods of sampling, simple random and one and two-way stratified, are studied in conjunction with estimators which use no population information, one and two sets of marginal frequencies and cell frequencies. It is shown that whether the information in the population frequencies is used in the sample draw or in the estimator, the…

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The Variance of an Estimator with Post-Stratified Weighting

后分层加权估计量的方差

A straightforward procedure is presented which uses the variance formula of a simple estimator to obtain an approximate formula for the variance of a post-stratified estimator. The approximation is the well-known one for the variance of a ratio estimator. The technique is applied to samples which have been selected in stratified and multistage designs and can be extended to other ratio estimators.

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The Variance of an Estimator with Post-Stratified Weighting

采用事后分层权重的估计量方差

A straightforward procedure is presented which uses the variance formula of a simple estimator to obtain an approximate formula for the variance of a post-stratified estimator. The approximation is the well-known one for the variance of a ratio estimator. The technique is applied to samples which have been selected in stratified and multistage designs and can be extended to other ratio estimators.

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On Two Methods of Unbiased Estimation with Auxiliary Variates

利用辅助变量进行无偏估计的两种方法

This paper shows the relationship between two existing methods of generating unbiased ratio and regression estimators. One procedure involves splitting up the population (theoretically) while the other splits up the sample itself. The two procedures yield similar estimators and are combinatorially equivalent. They are unalike in that they utilize different conditional arguments.

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On Two Methods of Unbiased Estimation with Auxiliary Variates

利用辅助变量进行无偏估计的两种方法

This paper shows the relationship between two existing methods of generating unbiased ratio and regression estimators. One procedure involves splitting up the population (theoretically) while the other splits up the sample itself. The two procedures yield similar estimators and are combinatorially equivalent. They are unalike in that they utilize different conditional arguments.

AI 解读阅读原文 ↗BibTeX ↓