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首页> 外文学位 >Predicting national data on the use of private vehicles in Canada for the 1980--1996 period: An application of the Bayesian approach of Gibbs sampling with data augmentation.
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Predicting national data on the use of private vehicles in Canada for the 1980--1996 period: An application of the Bayesian approach of Gibbs sampling with data augmentation.

机译：预测1980--1996年期间加拿大私家车使用的国家数据：吉布斯抽样的贝叶斯方法与数据增强的应用。

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摘要

An extended statistical software for the estimation, prediction, and inference of a wide variety of standard econometric models is developed to analyze datasets involving a large proportion of missing information. This relies on Bayesian sampling-based approaches with data augmentation. A generalization of the Bayesian treatment of vector autoregressive models is also considered. As a direct by-product, the proposed methodology is shown to be a natural and effective way to address the problem of data interpolation from intermittent longitudinal surveys which is both conceptually simple, and computationally tractable.; We apply the interpolation methodology to bridge the gap between two national surveys on the use of private vehicles which are six years apart. This allows us to produce quarterly predictions of the three energy components (the average number of vehicles, the average distance travelled by each vehicle, and their weighted fuel consumption rate) for the intermediary period, between the surveys. Separate estimates and predictions are obtained by vehicle type: for cars and for light trucks and vans. The same technique could also be directly implemented in other contexts such as international database comparisons, population censuses, longitudinal labour force surveys, etc.; First of all, survey-based estimates are adjusted with the aim of improving their compatibility. Predicted values for the intermediate period are obtained by means of the Bayesian method of Gibbs sampling with data augmentation. In order to improve efficiency, by making use of all available empirical information, the econometric model is estimated on the basis of data from both surveys, while taking into account the middle period, between the two surveys' sampling periods, for which no data exist.; Based on explanatory variables from external sources, the aggregate simultaneous equations model is formulated to account for the relationships among the energy components. The model takes into account the dynamics involved in the three dependent variable time series. Since the data are aggregated on a quarterly basis, it also captures seasonal variations, in addition to the general trends in the series.; Several alternative specifications are compared to determine the best prediction model. The generalized vector autoregressive model is shown to yield the most precise and reliable results. Convergence of the iterative estimation process and its dependence on prior choices are assessed by means of sensitivity analyses. Complete time series produced by this empirical analysis will provide more accurate data on which the policy makers can rely.; Given that a similar survey is to be done soon, the necessity of obtaining, from such intermittent sources, complete time series estimates for the key variables from a transportation researcher's point of view becomes crucial. However, the proposed interpolation methodology is not a substitute to a well-designed data collection process, but rather a general solution to existing data gaps.
机译：开发了用于各种标准计量经济学模型的估计，预测和推断的扩展统计软件，以分析涉及大量丢失信息的数据集。这依赖于具有数据增强功能的基于贝叶斯采样的方法。还考虑了矢量自回归模型的贝叶斯处理的一般化。作为直接的副产品，所提出的方法论是解决间歇性纵向勘测中数据插值问题的自然而有效的方法，这在概念上既简单又易于计算。我们采用插值方法来弥合相距六年的两次全国私人汽车使用调查之间的差距。这样一来，我们就可以在两次调查之间的中间期间，对三个能源成分（平均车辆数量，平均每辆车辆行驶的平均距离及其加权燃料消耗率）进行季度预测。根据车辆类型分别获得估计和预测：用于汽车以及轻型卡车和货车。同样的技术也可以在其他情况下直接实施，例如国际数据库比较，人口普查，纵向劳动力调查等；首先，对基于调查的估计值进行调整，以提高其兼容性。中间时段的预测值是通过具有数据增强功能的吉布斯采样的贝叶斯方法获得的。为了提高效率，通过利用所有可用的经验信息，基于两次调查的数据估算经济计量模型，同时考虑到两次调查的采样周期之间的中间时间段，而该中间期没有数据。;根据外部来源的解释性变量，建立了总联立方程模型，以说明各能量分量之间的关系。该模型考虑了三个因变量时间序列中涉及的动力学。由于数据是按季度汇总的，因此除了系列的总体趋势之外，它还捕获了季节性变化。比较了几种替代规范，以确定最佳预测模型。广义向量自回归模型显示出最精确和可靠的结果。通过敏感性分析来评估迭代估计过程的收敛性及其对先前选择的依赖性。通过这种经验分析得出的完整时间序列将为决策者提供更准确的数据。鉴于即将进行类似的调查，从运输研究者的角度出发，从这样的间歇性来源获得关键变量完整的时间序列估计的必要性变得至关重要。但是，建议的插值方法不能替代精心设计的数据收集过程，而是对现有数据缺口的一般解决方案。

著录项

  • 作者

    Boucher, Nathalie.;

  • 作者单位

    Queen's University at Kingston (Canada).;

  • 授予单位 Queen's University at Kingston (Canada).;
  • 学科 Economics General.; Transportation.; Statistics.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 201 p.
  • 总页数 201
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 经济学;综合运输;统计学;
  • 关键词

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