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似不相关回归模型贝叶斯分析的直接蒙特卡洛方法AI 解读

Computationally efficient methods for Bayesian analysis of seemingly unrelated regression (SUR) models are described and applied that involve the use of a direct Monte Carlo (DMC) approach to calculate Bayesian estimation and prediction results using diffuse or informative priors. This DMC approach is employed to compute Bayesian marginal posterior densities, moments, intervals and other quantities, using data simulated from known models and also using data from an empirical…

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计量经济学与统计学中的贝叶斯分析：Zellner 的观点与论文AI 解读

Part 1 Introduction. Part 2 Overview of Bayesian analysis. Part 3 Bayesian priors, models and information processing. Part 4 Bayesian methods. Part 5 Bayesian forecasting.

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Gibbs 抽样器的收敛判据AI 解读

This article presents new operational convergence criteria for the Gibbs sampler (GS) and related procedures that are useful for determining whether they not only have converged but also have converged to provide reliable results. Three GS convergence criteria are presented and applied: the difference convergence criterion (DC2), the ratio convergence criterion (RC2), and the anchored ratio convergence criterion (ARC2). Their uses and properties are discussed and examples…

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评 Otter《多元时间序列中的典型相关及一年期与多年期宏观预测应用》AI 解读

(1992). Comments on “Canonical Correlation in Multivariate Time Series Analysis With an Application to One-Year-Ahead and Multiyear- Ahead Macroeconomic Forecasting,” by P. W. Otter. Journal of Business & Economic Statistics: Vol. 10, No. 4, pp. 470-471.

对《多元时间序列分析中的典型相关及其在一年期与多年期宏观预测中的应用》的评论AI 解读

Arnold Zellner, Chansik Hong, Comments on "Canonical Correlation in Multivariate Time Series Analysis with an Application to One-Year-Ahead and Multiyear-Ahead Macroeconomic Forecasting," by P. W. Otter, Journal of Business & Economic Statistics, Vol. 10, No. 4 (Oct., 1992), pp. 470-471

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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AI 解读

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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非对称损失函数下的贝叶斯估计与预测AI 解读

Estimators and predictors that are optimal relative to Varian's asymmetric LINEX loss function are derived for a number of well-known models. Their risk functions and Bayes risks are derived and compared with those of usual estimators and predictors. It is shown that some usual estimators, for example, a scalar sample mean or a scalar least squares regression coefficient estimator, are inadmissible relative to asymmetric LINEX loss by providing alternative estimators that…

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