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An Interactive PC-Based Procedure for Reliability Assessment Incorporating Expert Opinion and Survival Data

结合专家意见与生存数据的交互式可靠性评估

In this article I present a new approach for the analysis of life-length data that can be described by a Weibull distribution. The novel feature of my approach pertains to the incorporation of informed judgment or expert opinion into the analysis, using a personal computer in an interactive and user-friendly manner. This approach also provides for incorporating the analyst's opinions on the expertise of the experts. Many of the analyses result in graphical displays, making…

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Robust Empirical Bayes Estimation of Means from Stratified Samples

分层样本均值的稳健经验贝叶斯估计

This article considers simultaneous estimation of means from several strata, where each stratum contains a finite number of elements. For example, quite often estimates of annual incomes, unemployment rates, and so forth must be made simultaneously for many areas. Our results find application in small area estimation where very few samples are available from an individual area, and an estimate of a certain area mean or simultaneous estimates of several area means can be…

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An Approach to Inference following Model Selection with Applications to Transformation-Based and Adaptive Inference

模型选择后推断:变换型与自适应推断的决策论方法

A decision-theory approach is formulated for inference following model selection. Inference here refers to either testing, point estimation, or confidence estimation. The loss function includes components for model selection as well as for inference and allows for flexibility in emphasis on one or the other, if such emphasis is desired. A general prescription for Bayes and generalized Bayes procedures is given. A procedure consists of model selection and inference. The…

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Computing Distributions for Exact Logistic Regression

精确 Logistic 回归所需分布的计算

Logistic regression is a commonly used technique for the analysis of retrospective and prospective epidemiological and clinical studies with binary response variables. Usually this analysis is performed using large sample approximations. When the sample size is small or the data structure sparse, the accuracy of the asymptotic approximations is in question. On other occasions, singularity of the covariance matrix of parameter estimates precludes asymptotic analysis. Under…

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The Power of the Mantel—Haenszel Test

Mantel–Haenszel 检验的功效

The Mantel-Haenszel (MH) test (Mantel and Haenszel 1959) is a widely used method for analyzing sets of two-by-two tables that compare the outcome of two treatments in several strata (Bailar and Anthony 1977). The procedure tests the null hypothesis of no partial association between treatment and outcome in any of the strata, or tables, against the alternative that the partial association, as measured by the common odds ratio, differs from 1. Birch (1964) showed that for a…

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Variance Function Estimation

方差函数估计

Heteroscedastic regression models are used in fields including economics, engineering, and the biological and physical sciences. Often, the heteroscedasticity is modeled as a function of the covariates or the regression and other structural parameters. Standard asymptotic theory implies that how one estimates the variance function, in particular the structural parameters, has no effect on the first-order properties of the regression parameter estimates; there is evidence,…

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Estimating Properties of Autoregressive Forecasts

自回归预测误差性质的估计

Forecasting requires estimates of the error of prediction; however, such estimates for autoregressive forecasts depend nonlinearly on unknown parameters and distributions. Substitution estimators of mean squared error (MSE) possess bias that varies with the underlying model, and Gaussian-based prediction intervals fail if the data are not normally distributed. This article proposes methods that avoid these problems. A second-order Taylor expansion produces an estimator of…

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Benchmarking of Economic Time Series

经济时间序列的基准校准

This article develops a statistical model-based approach to the benchmarking problem. Benchmarking is done when data from a monthly sample survey are combined with data from an annual census for the purpose of improving the survey estimates. Previous authors have used numerical analysis techniques to derive methods to perform benchmarking. This article formulates the benchmarking problem in a statistical framework and uses modern times series methods to derive a solution.…

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Best Approximate Aggregation of Input—Output Systems

投入产出系统的最优近似聚合

A method of constructing aggregate input—output systems is proposed. The procedure minimizes the mean squared error of aggregate predictions. The range of data on which the aggregate model is to be applied influences the best approximate aggregate. Best approximate aggregate models maximize Ijiri's coefficient of aggregation. In a special case, Fisher's aggregated model emerges: if consistent aggregation is possible it gives the best approximate aggregate. Computations…

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Time Series Analysis of a Contagious Process

传染性事件过程的时间序列分析

Between 1968 and 1972 there were 326 attempts to hijack aircraft worldwide, including 137 attempts in the United States. Those attempts were often attributed to imitation of previous hijacking incidents, and aircraft hijacking, like many other types of behavior, was described as a “contagious” phenomenon. In this article a general mathematical model is developed for serial dependence of rates at which events occur and is applied to data on the hijacking attempts in the U.S.…

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Restricted Mean Life with Adjustment for Covariates

考虑协变量调整的限制平均生存时间

Although the mean is the most widely used measure of location in comparing two distributions, its use is essentially precluded in the presence of substantial censoring, typical in survival analysis of medical therapies. To accommodate censoring, Irwin (1949) proposed estimation of the expectation of life restricted to a time T, using the actuarial estimator of the survival function. In this article we examine the restricted mean as an index for comparing survival in two…

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Inference and Prediction for a General Order Statistic Model with Unknown Population Size

总体规模未知的一般次序统计量模型:推断与预测

Suppose that the first n order statistics from a random sample of N positive random variables are observed, where N is unknown. This, the general order statistic model, has been applied to the study of market penetration, capture—recapture, burn-in in repairable systems, software reliability growth, the estimation of the number of individuals exposed to radiation, and the estimation of the number of unseen species. Inference is to be made about the unknown parameters,…

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Biased and Unbiased Cross-Validation in Density Estimation

密度估计中的有偏与无偏交叉验证

Nonparametric density estimation requires the specification of smoothing parameters. The demands of statistical objectivity make it highly desirable to base the choice on properties of the data set. In this article we introduce some biased cross-validation criteria for selection of smoothing parameters for kernel and histogram density estimators, closely related to one investigated in Scott and Factor (1981). These criteria are obtained by estimating L 2 norms of derivatives…

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The Efficiency of Multinomial Logistic Regression Compared with Multiple Group Discriminant Analysis

多项逻辑回归相对于多组判别分析的效率

Multinomial logistic regression (also referred to as polychotomous logistic regression) is frequently used for the analysis of categorical response data with continuous or categorical explanatory variables. Parameter estimates are usually obtained through direct maximum likelihood estimation. Normal discriminant analysis has been used as an alternative approach to this methodology, although it is strictly appropriate only when the usual normal discriminant assumptions…

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Analysis of Covariance Structures under Elliptical Distributions

椭圆分布下的协方差结构分析

This article examines the adjustment of normal theory methods for the analysis of covariance structures to make them applicable under the class of elliptical distributions. It is shown that if the model satisfies a mild scale invariance condition and the data have an elliptical distribution, the asymptotic covariance matrix of sample covariances has a structure that results in the retention of many of the asymptotic properties of normal theory methods. If a scale adjustment…

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Non-Gaussian State—Space Modeling of Nonstationary Time Series

非平稳时间序列的非高斯状态空间建模

A non-Gaussian state—space approach to the modeling of nonstationary time series is shown. The model is expressed in state—space form, where the system noise and the observational noise are not necessarily Gaussian. Recursive formulas of prediction, filtering, and smoothing for the state estimation and identification of the non-Gaussian state—space model are given. Also given is a numerical method based on piecewise linear approximation to the density functions for realizing…

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Tests of Forecast Accuracy and Bias for County Population Projections

美国县级人口预测的准确性与偏差检验

"This article deals with the forecast accuracy and bias of population projections for 2,971 counties in the United States. It uses three different projection techniques and data from 1950, 1960, 1970, and 1980 to make two sets of 10-year projections and one set of 20-year projections. These projections are compared with census counts to determine forecast errors. The size, direction, and distribution of forecast errors are analyzed by size of place, rate of growth, and…

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Census Undercount Adjustment and the Quality of Geographic Population Distributions

人口普查漏计调整与地理人口分布的质量

We develop a simulation procedure to measure the effects of synthetic adjustment for census undercounts on the quality of estimated proportionate geographic population distributions. Analyzing the influences of both interstate variations in census coverage and measurement errors in national undercount estimates, we find that, over a wide range of environments, nearly two out of every three simulated applications of synthetic adjustment improve the state proportions for a…

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Benefit-Cost Analysis of Data Used to Allocate Funds.

用于资金分配的数据的效益成本分析

0 Introduction.- 1 Loss Function and Benefit Measurement.- 1.0 Introduction.- 1.1 Utility and Social Welfare.- 1.2 Equity.- 1.3 A Simple Loss Function.- Errors in Allocation.- 1.4 Estimating the Parameters of the Loss Function L(f?,??) for GRS.- 1.5 Fisher-Consistency and Other Properties of the Loss Function L(f?,??).- 1.6 More General Loss Functions: LH(f?,??) , Lw(f?,??).- 1.7 Exponential Loss Functions.- 2 The Delta Method.- 2.0 Outline.- 2.1 Notation.- 2.2 Description…

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