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An empirical Bayes problem with a Markovian parameter

参数具有马尔可夫结构的经验贝叶斯问题

A study is made of an empirical Bayes estimation problem in which the set of parameter values is a realization of a stationary Markov chain. The Bayes rule is derived as a function of the transition probabilities of the Markov chain. The performance of empirical Bayes rules, which use estimates of these transition probabilities based on the observations, is investigated by simulation. Two other rules are shown to be competitors of the empirical Bayes rules in some particular…

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Optimal linear estimators: an empirical Bayes version with application to the binomial distribution

最优线性估计量的经验贝叶斯版本及其二项分布应用

An empirical Bayes estimator is one which estimates the posterior mean by making use of past data. For certain conditional distributions though, no empirical Bayes estimator can be found which converges to the posterior mean as past data are accumulated. However, an optimal linear estimator for a parameter, say θ1 can often be found. This optimal linear estimator depends upon the first two prior moments, both of which can often be estimated. The resulting estimator has been…

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Analysis of correlated random effects: linear model with two random components

相关随机效应分析:含两个随机分量的线性模型

Linear regression models with two random components, one of which is time correlated, are analysed from a Bayesian viewpoint. The problem of making inferences about the parameters when the time correlated component is stationary is discussed. Necessary modifications needed for nonstationary and explosive models are indicated. The analysis is illustrated by a numerical example showing that the time series component of the data can exert a strong influence in determining the…

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Optimal Regression Designs with Previous Observations

利用既有观测的最优回归设计

A method is developed for constructing D-optimal designs in a linear regression context with k explanatory variables, when previous observations are available and a fixed number of new sets of values of the explanatory variables are to be chosen within the unit sphere. The effect of previous observations on the relationship between D-optimality and E-opti-mality is discussed. The relationship between designs constructed sequentially to be optimum for each new set of values…

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Analysis of Distributed Lag Models with Applications to Consumption Function Estimation

分布滞后模型分析及其在消费函数估计中的应用

SINCE KOYCK'S pioneering work, distributed lag models have come to play an important role in econometrics and much work has been done to develop methods for analyzing them-see e.g. Koyck [15], Klein [12], Solow [20], Fuller and Martin [5], Malinvaud [18], Hannan [9], Liviatan [17], Amemiya and Fuller [1], Zellner and Park [25], Thornber [21], Waud [23], Dhrymes [3], and Griliches [7]. In the present paper we present maximum likelihood and Bayesian estimation procedures for…

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The Measurement of Association in a Contingency Table: Three Extensions of the Cross-Ratios and Metrics Methods

列联表关联度量:交叉比与度量方法的三项扩展

Summary The methods of cross-ratios, equivalence classes and metrics that were introduced in a previous paper (Altham 1970) are extended to three further problems. First the interdependence of the rows, columns and layers of a three-way contingency table is discussed. There are essentially four different types of association to be considered: the complete dependence of rows, columns and layers, the dependence of rows and columns conditional on a given layer, the dependence…

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Calibration and Statistical Inference

校准与统计推断

This article presents an elementary statistical model from which inferences in the form of probability statements are drawn. These are compared with the inferences derived from the corresponding classical and Bayesian models of the same phenomenon. The example concerns a measuring device, and the problem of calibration is discussed. The method of analysis extends to a wide range of common statistical applications, notably those described by multivariate and linear regression…

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Calibration and Statistical Inference

校准与统计推断

This article presents an elementary statistical model from which inferences in the form of probability statements are drawn. These are compared with the inferences derived from the corresponding classical and Bayesian models of the same phenomenon. The example concerns a measuring device, and the problem of calibration is discussed. The method of analysis extends to a wide range of common statistical applications, notably those described by multivariate and linear regression…

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Application of Likelihood Methods to Models Involving Large Numbers of Parameters

似然方法在含大量参数模型中的应用

Summary Likelihood methods of dealing with some multiparameter problems are introduced and exemplified. Specifically, methods of eliminating nuisance parameters from the likelihood function so that inferences can be made about the parameters of interest are considered. In this regard integrated likelihoods, maximum relative likelihoods, conditional likelihoods, marginal likelihoods and second-order likelihoods are introduced and their uses illustrated in examples. Marginal…

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Optimal Design of Sampling from Finite Populations: A Critical Review and Indication of New Research Areas

有限总体抽样的最优设计:批判性综述与新研究方向

The design of sampling from finite populations is receiving increased attention in the statistical literature. This article presents a critical review of past studies and new developments and outlines areas meriting further study and research. Bayesian and non-Bayesian approaches are analyzed but are not offered in a normative manner. Both points of view and the extent to which they provide differences in survey sample design are discussed and examined. These differences are…

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Optimal Design of Sampling from Finite Populations: A Critical Review and Indication of New Research Areas

有限总体抽样的最优设计:批判性综述与新研究方向

The design of sampling from finite populations is receiving increased attention in the statistical literature. This article presents a critical review of past studies and new developments and outlines areas meriting further study and research. Bayesian and non-Bayesian approaches are analyzed but are not offered in a normative manner. Both points of view and the extent to which they provide differences in survey sample design are discussed and examined. These differences are…

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Supplementary sample nonparametric empirical Bayes in a quality control situation

质量控制中的补充样本非参数经验贝叶斯方法

The supplementary sample nonparametric empirical Bayes procedure (Krutchkoff, 1967) is slightly modified here and compared with the classical quality control procedure by Monte Carlo simulation. It is found that the empirical Bayes procedure is generally more powerful and will usually detect an out-of-control situation sooner than the classical procedure.

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Supplementary Sample Nonparametric Empirical Bayes in a Quality Control Situation

质量控制中的补充样本非参数经验贝叶斯方法

The supplementary sample nonparametric empirical Bayes procedure (Krutchkoff, 1967) is slightly modified here and compared with the classical quality control procedure by Monte Carlo simulation. It is found that the empirical Bayes procedure is generally more powerful and will usually detect an out-of-control situation sooner than the classical procedure.

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A Bayesian Look at Inverse Linear Regression

逆线性回归的贝叶斯视角

The model considered in this paper is simple linear regression , and the problem is to make statistical inferences about an unknown value of x corresponding to one or more additional observed values of y. The maximum likelihood estimator x of x and the classical (1 - α) 100% confidence set S for x have some undesirable properties. For example, has infinite mean square error and > 0. The purpose of this paper is to demonstrate that insight and understanding, as well as a…

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Selecting One of Two Treatments When the Responses are Dichotomous

二元治疗反应下的两种疗法选择

A decision theoretic approach to the design of a clinical trial is considered for the situation in which a total of N patients with a disease receive one of two treatments and the responses to the treatments are dichotomous. Two costs are considered: The cost of treating a patient with the inferior treatment and the cost of conducting the trial. Minimax and Bayes procedures are used to determine the optimum size of a fixed sample trial. Bayes solutions for the optimum sample…

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Optimal regression designs with previous observations

利用既有观测的最优回归设计

A method is developed for constructing D-optimal designs in a linear regression context with k explanatory variables, when previous observations are available and a fixed number of new sets of values of the explanatory variables are to be chosen within the unit sphere. The effect of previous observations on the relationship between D-optimality and E-opti-mality is discussed. The relationship between designs constructed sequentially to be optimum for each new set of values…

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‘The use of empirical Bayes estimators in a linear regression model’

《线性回归模型中经验贝叶斯估计量的使用》公式订正条目

In (18) the quantity summed in the numerator should read and the definition of At should read (β – βi+h)/(2h). In (19) a plus sign should be inserted on the right hand side after β Exactly corresponding changes should be made in the numerator of (21) and in the definition of Ci In (30) the last term on the right hand side should read (x-x¯)2E(β-β)2.

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A Class of Sequential Tests for an Exponential Parameter

指数分布参数的一类序贯检验

Weiss [5] and Freeman and Weiss [2] have shown how to construct sampling plans which at least approximately minimize the maximum expected sample size in the case of Bernoulli and Normal populations. In this paper we construct sequential procedures of this type for the testing of an exponential parameter. An invariance property of the stopping region is presented which simplifies the construction of the Bayes regions. Several sampling plans are given and some of their…

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Mean Square Efficiency of Estimators of Variance Components

方差分量估计量的均方误差效率

Various estimators of components of variance for the balanced one way layout are compared using mean squared error as a measure of performance. Several modifications of the maximum likelihood estimator and several formal Bayes estimators are compared and mean square error relationships are given. Inadmissibility is established for a large class of translation and scale invariant estimators. Numerical results are tabled and graphed to exhibit the relative efficiency of the…

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