摘要翻译:
本文提出了一个具有多元随机波动率的贝叶斯向量自回归(VAR)模型,该模型能够处理海量信息集。为了保证模型的可靠估计,引入了三个特征。首先,我们假设VAR中的简化形式误差具有因子随机波动率结构,允许条件方程逐方程估计。其次,我们将最近发展起来的全局-局部收缩先验值应用于VAR系数,以消除维数的诅咒。第三,我们利用最近的创新来有效地从高维多元高斯分布中采样。这使得在维数较大但时间序列长度适中的情况下,基于仿真的完全贝叶斯推理是可行的。我们在一个广泛的模拟研究中证明了我们的方法的优点,并将该模型应用于美国宏观经济数据来评估其预测能力。
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英文标题:
《Sparse Bayesian vector autoregressions in huge dimensions》
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作者:
Gregor Kastner and Florian Huber
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最新提交年份:
2019
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分类信息:
一级分类:Statistics 统计学
二级分类:Computation 计算
分类描述:Algorithms, Simulation, Visualization
算法、模拟、可视化
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一级分类:Economics 经济学
二级分类:Econometrics 计量经济学
分类描述:Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论,微观计量经济学,宏观计量经济学,通过新方法发现的经济关系的实证内容,统计推论应用于经济数据的方法论方面。
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一级分类:Statistics 统计学
二级分类:Applications 应用程序
分类描述:Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学,教育学,流行病学,工程学,环境科学,医学,物理科学,质量控制,社会科学
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一级分类:Statistics 统计学
二级分类:Methodology 方法论
分类描述:Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计,调查,模型选择,多重检验,多元方法,信号和图像处理,时间序列,平滑,空间统计,生存分析,非参数和半参数方法
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英文摘要:
We develop a Bayesian vector autoregressive (VAR) model with multivariate stochastic volatility that is capable of handling vast dimensional information sets. Three features are introduced to permit reliable estimation of the model. First, we assume that the reduced-form errors in the VAR feature a factor stochastic volatility structure, allowing for conditional equation-by-equation estimation. Second, we apply recently developed global-local shrinkage priors to the VAR coefficients to cure the curse of dimensionality. Third, we utilize recent innovations to efficiently sample from high-dimensional multivariate Gaussian distributions. This makes simulation-based fully Bayesian inference feasible when the dimensionality is large but the time series length is moderate. We demonstrate the merits of our approach in an extensive simulation study and apply the model to US macroeconomic data to evaluate its forecasting capabilities.
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PDF链接:
https://arxiv.org/pdf/1704.03239