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统计过程控制中的时间序列建模AI 解读

In statistical process control, a state of statistical control is identified with a process generating independent and identically distributed random variables. It is often difficult in practice to attain a state of statistical control in this strict sense; autocorrelations and other systematic time-series effects are often substantial. In the face of these effects, standard control-chart procedures can be seriously misleading. We propose and illustrate statistical modeling…

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对《反向回归、公平性与就业歧视》评论的再回应AI 解读

(1984). Rejoinder to Comments on “Reverse Regression, Fairness, and Employment Discrimination”. Journal of Business & Economic Statistics: Vol. 2, No. 2, pp. 126-139.

对《反向回归、公平性与就业歧视》评论的答复AI 解读

Delores A. Conway, Harry V. Roberts, Rejoinder to Comments on "Reverse Regression, Fairness, and Employment Discrimination", Journal of Business & Economic Statistics, Vol. 2, No. 2 (Apr., 1984), pp. 126-139

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反向回归、公平与就业歧视AI 解读

Possible salary discrimination can be studied by comparing mean salaries of, say, males and females, after statistical adjustment for differences in job qualifications. The adjustment is often made by regression, with salary as dependent variable, and job qualifications and sex as independent variables. One might also regress job qualifications on salary and sex, a procedure called reverse regression. Ideas about fairness as well as technical concepts are relevant to…

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通过识别法求取抽样分布AI 解读

Let [ttilde] be a statistic sufficient for a parameter θ and let L[θ;t) be the likelihood function of θ for given t. Suppose we recognize a function φ(t) such that L(θ;t) φ(t) regarded as a function of t for a given θ, is a density function. We show here that this is the sampling density of [ttilde] if the family of recognized densities is complete. Examples are given to illustrate that in many situations this recognition method provides a neat way of finding sampling…

用识别法求抽样分布AI 解读

Let [ttilde] be a statistic sufficient for a parameter θ and let L[θ;t) be the likelihood function of θ for given t. Suppose we recognize a function φ(t) such that L(θ;t) φ(t) regarded as a function of t for a given θ, is a density function. We show here that this is the sampling density of [ttilde] if the family of recognized densities is complete. Examples are given to illustrate that in many situations this recognition method provides a neat way of finding sampling…

信息性停止规则与总体规模推断AI 解读

It is a consequence of the likelihood principle that identical likelihood functions imply identical inferences. If the rule by which sample size is determined—the stopping rule—is reflected in the likelihood function, as it should be, apparently identical likelihood functions (without allowance for stopping rule) may in fact be different. This can happen if the stopping rules are informative. If the stopping rule is informative, the analysis must take the rule into account,…

信息性停止规则与总体规模推断AI 解读

It is a consequence of the likelihood principle that identical likelihood functions imply identical inferences. If the rule by which sample size is determined—the stopping rule—is reflected in the likelihood function, as it should be, apparently identical likelihood functions (without allowance for stopping rule) may in fact be different. This can happen if the stopping rules are informative. If the stopping rule is informative, the analysis must take the rule into account,…

概率预测AI 解读

The posterior distribution for parameters of a data distribution is usually the major objective of a Bayesian statistical analysis. Relatively little attention has been given to the fact that either a prior or a posterior distribution implies a marginal distribution, which may be called a “predictive distribution,” for outcomes of any sample not yet observed. Predictive distributions have been mainly applied to design problems, such as determination of optimal sample size.…

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