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随机趋势、确定性趋势与经济周期转折点AI 解读

This study examines the relationship between specifications for long-run output patterns and specifications for business cycle dynamics. In an application to US GDP, it is found that inferences about the nature of the trend in output are not robust to changes in the specification for short-run fluctuations. Similarly, the choice of which model best describes the transitory movements in output depends on the way in which the trend is specified. The empirical analysis makes…

随机趋势、确定性趋势与经济周期转折点AI 解读

This study examines the relationship between specifications for long-run output patterns and specifications for business cycle dynamics. In an application to US GDP, it is found that inferences about the nature of the trend in output are not robust to changes in the specification for short-run fluctuations. Similarly, the choice of which model best describes the transitory movements in output depends on the way in which the trend is specified. The empirical analysis makes…

Bonferroni 调整的贝叶斯视角AI 解读

Bayes/frequentist correspondences between the p-value and the posterior probability of the null hypothesis have been studied in univariate hypothesis testing situations. This paper extends these comparisons to multiple testing and in particular to the Bonferroni multiple testing method, in which p-values are adjusted by multiplying by k, the number of tests considered. In the Bayesian setting, prior assessments may need to be adjusted to account for multiple hypotheses,…

通过全局与局部参数独立性刻画 Dirichlet 分布AI 解读

We provide a new characterization of the Dirichlet distribution. Let $\theta_{ij}, 1 \leq i \leq k, 1 \leq j \leq n$, be positive random variables that sum to unity. Define $\theta_{i \cdot} = \Sigma_{j=1}^n \theta_{ij}, \theta_{I \cdot} = {\theta_{i \cdot}_{i=1}^{k-1}, \theta_{j|i} = \theta_{ij}/ \Sigma_j \theta_{ij}$ and \theta_{J|i} = {\theta_{j|i}}_{j=1}^{n-1}$. We prove that if ${\theta_{I \cdot}, \theta_{J|1}, \dots, \theta_{J|k}}$ are mutually independent and ${\theta_{\cdot J}, \theta_{I|1}, \dots, \theta_{I|n}}$…

利用 Gibbs 抽样对含冗余设计的相干系统进行贝叶斯非参数估计AI 解读

We consider a coherent system S consisting of m independent components for which we do not know the distributions of the components' lifelengths. If we know the structure function of the system, then we can estimate the distribution of the system lifelength by estimating the distributions of the lifelengths of the individual components. Suppose that we can collect data under the "autopsy model," wherein a system is run until a failure occurs and then the status (functioning…

众数位于边界时贝叶斯因子的近似AI 解读

Bayes factors, measuring the strength of evidence in favor of the null, are often used in the Bayesian approach to testing hypotheses. Laplace approximations to Bayes factors are convenient and quite accurate in many contexts. However, one usual assumption—the existence of an interior mode—does not always hold. The posterior mode can occur at the boundary of the parameter space. This article discusses the boundary mode Laplace's method for boundary modes, uses it to…

利用后验模拟与Laplace–Metropolis估计量估计贝叶斯因子AI 解读

The key quantity needed for Bayesian hypothesis testing and model selection is the integrated, or marginal, likelihood of a model. We describe a way to use posterior simulation output to estimate integrated likelihoods. We describe the basic Laplace—Metropolis estimator for models without random effects. For models with random effects, we introduce the compound Laplace-Metropolis estimator. We apply this estimator to data from the World Fertility Survey and show it to give…

通过条件高斯动态模型进行多项时间序列的贝叶斯预测AI 解读

We consider inference in the class of conditionally Gaussian dynamic models for nonnormal multivariate time series. In such models, data are represented as drawn from nonnormal sampling distributions whose parameters are related both through time and hierarchically across several multivariate series. A key example—the main focus here—is time series of multinomial observations, a common occurrence in sociological and demographic studies involving categorical count data.…

层级泊松回归建模AI 解读

The Poisson model and analyses here feature nonexchangeable gamma distributions (although exchangeable following a scale transformation) for individual parameters, with standard deviations proportional to means. A relatively uninformative prior distribution for the shrinkage values eliminates the ill behavior of maximum likelihood estimators of the variance components. When tested in simulation studies, the resulting procedure provides better coverage probabilities and…

神经传递分析中的层级混合模型AI 解读

Hierarchically structured mixture models are studied in the context of data analysis and inference on neural synaptic transmission characteristics in mammalian, and other, central nervous systems. Mixture structures arise due to uncertainties about the stochastic mechanisms governing the responses to electrochemical stimulation of individual neurotransmitter release sites at nerve junctions. Models attempt to capture such scientific features as the sensitivity of individual…

昼夜节律的受限检验AI 解读

In medical applications there is interest in whether deaths or other events occur randomly throughout the day, as opposed to in a definite circadian pattern. At times, knowledge of the circadian phenomenon will suggest that a single cluster of events should occur during a specific period during the day, such as mid-morning. We propose a test that incorporates such knowledge. The test can be viewed as the likelihood ratio test for a restricted alternative for data from the…

二维列联表关联结构的贝叶斯检验与估计AI 解读

In a two-way contingency table, one is interested in checking the goodness of fit of simple models such as independence, quasi-independence, symmetry, and constant association, and estimating parameters that describe the association structure of the table. In a large table, one may be interested in detecting a few outlying cells that deviate from the main association pattern in the table. Bayesian tests of these hypotheses are described using a prior defined on the set of…

统计推断工具：后验分布与似然函数的探索方法AI 解读

A unified introduction to a variety of computational algorithms for likelihood and Bayesian inference. This third edition expands the discussion of many of the techniques presented, and includes additional examples as well as exercise sets at the end of each chapter.

昼夜节律的受限检验AI 解读

In medical applications there is interest in whether deaths or other events occur randomly throughout the day, as opposed to in a definite circadian pattern. At times, knowledge of the circadian phenomenon will suggest that a single cluster of events should occur during a specific period during the day, such as mid-morning. We propose a test that incorporates such knowledge. The test can be viewed as the likelihood ratio test for a restricted alternative for data from the…

二维列联表关联的贝叶斯检验与估计AI 解读

In a two-way contingency table, one is interested in checking the goodness of fit of simple models such as independence, quasi-independence, symmetry, and constant association, and estimating parameters that describe the association structure of the table. In a large table, one may be interested in detecting a few outlying cells that deviate from the main association pattern in the table. Bayesian tests of these hypotheses are described using a prior defined on the set of…

众数位于边界时的贝叶斯因子近似AI 解读

Bayes factors, measuring the strength of evidence in favor of the null, are often used in the Bayesian approach to testing hypotheses. Laplace approximations to Bayes factors are convenient and quite accurate in many contexts. However, one usual assumption—the existence of an interior mode—does not always hold. The posterior mode can occur at the boundary of the parameter space. This article discusses the boundary mode Laplace's method for boundary modes, uses it to…

摘要暂缺

神经传递分析中的层级混合模型AI 解读

Hierarchically structured mixture models are studied in the context of data analysis and inference on neural synaptic transmission characteristics in mammalian, and other, central nervous systems. Mixture structures arise due to uncertainties about the stochastic mechanisms governing the responses to electrochemical stimulation of individual neurotransmitter release sites at nerve junctions. Models attempt to capture such scientific features as the sensitivity of individual…

摘要暂缺

摘要暂缺

拍卖与议价：秘密保留价木材拍卖的计量研究AI 解读

This article considers a first-price sealed-bid auction at which the seller's reservation price is not announced in advance. We allow for a second round of bargaining and consider the Nash bargaining outcome when the object is unsold after the auctioning round. We characterize the bidders' and seller's Bayesian Nash equilibrium strategies. The distributions of the buyers' and seller's private values are estimated by nonlinear least squares from auction data on standing…

最优求职模型中的精确结构推断AI 解读

This paper is a study of the exact posterior distributions of parameters in a stationary optimal job search model. The author exploits the simple latent structure of the search model when all job offers are observed to stimulate posterior distributions of structural parameters when the latent structure is imperfectly observed. These simulations enable him to show the unusual shape of the job search likelihood when the data are durations and accepted wages. The author also…

封闭总体规模估计的贝叶斯方法AI 解读

A Bayesian methodology for estimating the size of a closed population from multiple incomplete administrative lists is proposed. The approach allows for a variety of dependence structures between the lists, can make use of covariates, and explicitly accounts for model uncertainty. Interval estimates from this approach are compared to frequentist and previously published Bayesian approaches. Several examples are considered.

Logistic 回归的层级贝叶斯半参数方法AI 解读

A simple procedure is proposed for exact computation to smooth Bayesian estimates for logistic regression functions, when these are not constrained to lie on a fitted regression surface. Exact finite sample inferences and predictions are available, together with an exact residual analysis. The prior distribution relates to O'Hagan's assumptions for a normal regression function. A global shrinkage parameter and local smoothness parameter can be evaluated from the current data…