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使用贝叶斯向量自回归进行预测：五年经验AI 解读

The results obtained in five years of forecasting with Bayesian vector autoregressions (BVAR's) demonstrate that this inexpensive, reproducible statistical technique is as accurate, on average, as those used by the best known commercial forecasting services. This article considers the problem of economic forecasting, the justification for the Bayesian approach, its implementation, and the performance of one small BVAR model over the past five years.

不同技术的预测准确性：美国宏观经济预测比较——Litterman 评论AI 解读

Robert B. Litterman, [Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts]: Comment, Journal of Business & Economic Statistics, Vol. 4, No. 1 (Jan., 1986), pp. 17-19

使用贝叶斯向量自回归进行预测：五年经验AI 解读

The results obtained in five years of forecasting with Bayesian vector autoregressions (BVAR's) demonstrate that this inexpensive, reproducible statistical technique is as accurate, on average, as those used by the best known commercial forecasting services. This article considers the problem of economic forecasting, the justification for the Bayesian approach, its implementation, and the performance of one small BVAR model over the past five years.

经济预测的统计方法AI 解读

A recently developed statistical model, called Bayesian vector autoregression, has proven to be a useful tool for economic forecasting. Such a model today forecasts a strong resurgence of growth in the second half of 1985 and in 1986.

用于时间序列分配的随机游走—马尔可夫模型AI 解读

This article describes a technique for distributing quarterly time series across monthly values. The method generalizes an approach described by Fernández (1981). The article also presents results of a test of the accuracy of these two approaches and of the accuracy of two standard procedures suggested by Chow and Lin (1971).