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贝叶斯:贝叶斯建模、后验推断与 MCMC。
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Fully Coherent Inference

完全相干推断

In a general setting in which prior distributions that may take on the value $\infty$ are admitted, an inference based on a posterior for a prior, $\mu$, that is "minimally compatible" with the inference is shown to have a strong property of expectation consistency, that implies a corresponding property of coherence: A nonnegative expected payoff function for a gambler's strategy is necessary 0 almost everywhere $(\mu)$. In the converse direction, under appropriate…

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An Approach to Robust Bayesian Analysis for Multidimensional Parameter Spaces

多维参数空间中的稳健贝叶斯分析方法

In some multiparameter Bayesian problems the prior is more naturally described as a joint density for all of the parameters and in others it is more naturally described as a product of marginal and conditional densities. Although ordinary quantile, ε-contamination, and density-ratio classes of priors may be sensible choices for robust Bayesian analyses in the former case, they may be less satisfactory in the latter. This article shows how to construct product classes of…

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Structural Image Restoration through Deformable Templates

通过可变形模板进行结构图像复原

Prior knowledge on the space of possible images is given in the form of a function or template in some domain. The set of all possible true images is assumed to be formed by a composition of that function with continuous mappings of the domain into itself. A prior Gaussian distribution is given on the set of continuous mappings. The observed image is assumed to be a degradation of the true image with additive noise. Given the observed image, a posterior distribution is then…

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Sensitivity in Bayesian Statistics: The Prior and the Likelihood

贝叶斯统计中的敏感性:先验与似然

One paradigm for sensitivity analyses in Bayesian statistics is to specify Γ, a reasonable class of priors, and to compute the corresponding class of posterior inferences. The class Γ is chosen to represent uncertainty about the prior. There is often additional uncertainty, however, about the family of sampling distributions. This article introduces a method for computing ranges of posterior expectations over reasonable classes of sampling distributions that lie “close to” a…

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A Bayesian View of Nominal Money and Real Output Through a New Classical Macroeconomic Window

新古典宏观框架下名义货币与实际产出的贝叶斯分析

This study investigates the empirical evidence on the effects of unanticipated changes in nominal money on real output in 47 countries when viewed through a window (i.e., likelihood function) that assumes the neutrality of anticipated changes. Using a Bayesian predictivist approach, it provides a pedagogical Bayesian analysis of generated regressor models in the face of specification uncertainty involving, among other things, multiple unit root and trend stationary…

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[A Bayesian View of Nominal Money and Real Output through a New Classical Macroeconomic Window]: Comment

透过新古典宏观视角看名义货币与实际产出的贝叶斯分析:评论

Bruce M. Hill, [A Bayesian View of Nominal Money and Real Output through a New Classical Macroeconomic Window]: Comment, Journal of Business & Economic Statistics, Vol. 9, No. 2 (Apr., 1991), pp. 149-150

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Asymptotic Optimality of Bayes Compound Estimators in Compact Exponential Families

紧参数空间指数族中贝叶斯复合估计量的渐近最优性

The problem of finding admissible, asymptotically optimal compound rules is pursued in the infinite state case. The components involve the estimation of an arbitrary continuous transform of the natural parameter of a real exponential family with compact parameter space. We show that all Bayes estimators are admissible. Our main result is that any Bayes compound estimator versus a mixture of i.i.d. priors on the compound parameter is asymptotically optimal if the mixing…

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On the Consistency of Posterior Mixtures and Its Applications

后验混合分布的一致性及其应用

Consider i.i.d. pairs $(\theta_i, X_i), i \geq 1$, where $\theta_1$ has an unknown prior distribution $\omega$ and given $\theta_1, X_1$ has distribution $P_{\theta_1}$. This setup arises naturally in the empirical Bayes problems. We put a probability (a hyperprior) on the space of all possible $\omega$ and consider the posterior mean $\hat{\omega}$ of $\omega$. We show that, under reasonable conditions, $P_{\hat{\omega}} = \int P_\theta d\hat{\omega}$ is consistent in $L_1$.…

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Coherent Statistical Inference and Bayes Theorem

相容统计推断与贝叶斯定理

Conditions are given which suffice for the assessment of a coherent inference by means of a Bayesian algorithm, i.e., a suitable extension of the classical Bayes theorem relative to a finite number of alternatives. Under some further hypotheses such inference is shown to be, in addition, coherent in the sense of Heath, Lane and Sudderth. Moreover, a characterization of coherent posteriors is provided, together with some remarks concerning finitely additive conditional…

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Generalized Linear Models with Random Effects; a Gibbs Sampling Approach

含随机效应的广义线性模型:Gibbs 抽样方法

Generalized linear models have unified the approach to regression for a wide variety of discrete, continuous, and censored response variables that can be assumed to be independent across experimental units. In applications such as longitudinal studies, genetic studies of families, and survey sampling, observations may be obtained in clusters. Responses from the same cluster cannot be assumed to be independent. With linear models, correlation has been effectively modeled by…

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Review Papers: Modeling Capture, Recapture, and Removal Statistics for Estimation of Demographic Parameters for Fish and Wildlife Populations: Past, Present, and Future

综述:鱼类与野生动物种群参数的捕获、再捕获及移除建模

In this article I review the modeling of capture, recapture, and removal statistics for the purpose of estimating demographic parameters of fish and wildlife populations. Topics considered include capture-recapture models, band or tag return models, removal and catch per unit effort models, selective removal or change-in-ratio models, radio-tagging survival models, and nest survival models. The purpose is to present important concepts in a general manner for the benefit of a…

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Semiparametric Estimation in the Rasch Model and Related Exponential Response Models, Including a Simple Latent Class Model for Item Analysis

Rasch及相关指数响应模型的半参数估计与潜类别分析

The Rasch model for item analysis is an important member of the class of exponential response models in which the number of nuisance parameters increases with the number of subjects, leading to the failure of the usual likelihood methodology. Both conditional-likelihood methods and mixture-model techniques have been used to circumvent these problems. In this article, we show that these seemingly unrelated analyses are in fact closely linked to each other, despite dramatic…

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Multiple Imputation of Industry and Occupation Codes in Census Public-use Samples Using Bayesian Logistic Regression

用贝叶斯逻辑回归多重插补人口普查行业与职业编码

We describe methods used to create a new Census data base that can be used to study comparability of industry and occupation classification systems. This project represents the most extensive application of multiple imputation to date, and the modeling effort was considerable as well—hundreds of logistic regressions were estimated. One goal of this article is to summarize the strategies used in the project so that researchers can better understand how the new data bases were…

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Bayesian and Frequentist Predictive Inference for the Patterns of Care Studies

医疗照护模式研究中的贝叶斯与频率学派预测推断

The Patterns of Care Studies were conducted to determine the quality of care received by cancer patients whose primary treatment modality is radiation therapy. In this article, we propose and evaluate models which, if acceptable, permit Bayesian and frequentist model-based predictive inference for the desired finite population parameters. Using both hierarchical Bayesian and frequentist mixed linear models, we describe methodology for making the desired inferences,…

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Bayesian and Likelihood Methods in Statistics and Econometrics: Essays in Honor of George A. Barnard.

统计与计量经济学中的贝叶斯和似然方法:向乔治·A.巴纳德致敬的论文集

Introduction. A Survey of George Barnard's Statistical Work. (D.V. Lindley). Foundations (Contributors: A.P. Dempster B.M. Hill J.S. Hodges D.A. Lane). Selected Applications (Contributors: S. Chib, S.R. Jammalamadaka, R.C. Tiwari L. Denby, R. Gnanadesikan, J.R. Kettenring, J.W. Suzansky S.E. Fienberg Y. Hiatovsky H. Tsurumi). Selected Inference Problems (Contributors: M.J. Bayarri, M.H. DeGroot L.D. Broemeling, M.S. Son, H.I. Hamdy C.-H. Chen, J.M. Dickey G.T. Duncan M.…

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Bayesian and Frequentist Predictive Inference for the Patterns of Care Studies

医疗照护模式研究中的贝叶斯与频率学派预测推断

The Patterns of Care Studies were conducted to determine the quality of care received by cancer patients whose primary treatment modality is radiation therapy. In this article, we propose and evaluate models which, if acceptable, permit Bayesian and frequentist model-based predictive inference for the desired finite population parameters. Using both hierarchical Bayesian and frequentist mixed linear models, we describe methodology for making the desired inferences,…

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Bayesian Implementation

贝叶斯实施

The decentralization of decision-making is analyzed when agents may have information that is incomplete and possibly exclusive. Theorems provide conditions under which there exists a mechanism whose Bayesian equilibria coincide with a desired collection of social choice functions. The first theorem characterizes Bayesian implementation in economic environments with three or more individuals. The second theorem extends the analysis to noneconomic environments. An example…

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Grouped Likelihood for the Shifted Power Transformation

平移幂变换模型的分组似然

SUMMARY Estimation of parameters is considered in the shifted power transformation family of models. The ordinary likelihood function is shown to behave poorly, often having no local maximum. It is argued that a grouped likelihood approach avoids these difficulties, and the practical implementation of this approach is considered. Bayesian inference is also considered, though more briefly, and it is argued that there are again difficulties with an ungrouped likelihood…

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Bayesian Inference for Medical Screening Tests: Approximations Useful for the Analysis of Acquired Immune Deficiency Syndrome

医学筛查检验的贝叶斯推断:艾滋病分析中的实用近似

SUMMARY In this paper, we develop large sample Bayesian methods for assessing the accuracy of screening tests that are used to detect antibodies to the human immunodeficiency virus in donated blood, and for assessing the prevalence of the disease in the population sampled from. We obtain approximate joint and marginal posterior distributions for the predictive values positive and negative of a test and, additionally, we obtain approximate predictive distributions for the…

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