Models for Dependent Time Series
Models for Dependent Time Series
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相关时间序列模型
DOI：
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发表时间：
2015
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通讯作者：
J. Haywood
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文献类型：
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作者：
G. T. Wilson;M. Reale;J. Haywood
简介和概述 时间序列示例 时间序列内和时间序列之间的依赖性 时间序列建模的一些挑战 反馈和周期 高频采样的挑战 因果建模和结构 一些实际考虑因素 滞后回归和自回归模型 平稳离散时间序列和相关性 时间序列的自回归近似 多步自回归模型预测 自回归模型近似示例 多元自回归模型 高提前期预测的自回归 模型脉冲响应函数 VAR 的协方差模型 VAR 模型的偏相关性 VAR 模型的逆协方差 自回归移动平均模型 VAR 模型的状态空间表示 使用协方差矩阵进行投影 VAR 模型的滞后响应函数 相关序列的频谱分析 时间序列的谐波分量 周期和滞后 周期和平稳性 时间序列的频谱和交叉频谱 谐波分量之间的相关性 双变量和多变量频谱特性 频谱特性估计 样本协方差和平滑频谱逐渐变细和预白化 谱分析的实例 大样本中的谐波对比 向量自回归的估计 估计方法 VAR 模型的频谱 VAR(p) 模型的 Yule-Walker 估计 通过滞后回归估计 VAR(p) 最大似然估计，具有外生变量的 MLE VAR 模型，VARX 时间序列模型的 Whittle 似然 结构 VAR 的图形建模 结构 VAR、SVAR 有向无环图， DAG 条件独立图，CIG CIG 的解释 CIG 的特性 DAG 的估计和选择 构建结构 VAR、SVAR 偏相关图的特性 联立方程建模 生猪市场的 SVAR 模型：创新 生猪市场系列的完整 SVAR 模型 VZAR：VAR 模型的扩展 贴现过去 广义移位算子 VZAR 模型 VZAR 模型的属性 通过 VZAR 近似过程VZAR 的模型 Yule-Walker 拟合 VZAR 的回归拟合 VZAR 的最大似然拟合 VZAR 模型评估 连续时间 VZAR 模型 连续时间序列 连续时间自回归和 CAR(1) CAR(p) 模型 连续时间广义平移 连续时间 VZAR 模型、VCZAR VCZAR 模型的属性 通过 VCZAR 近似连续过程 VCZAR 模型的 Yule-Walker 拟合VCZAR 的回归和 ML 估计 不规则采样序列 不规则采样序列建模 不规则采样数据的似然性 不规则采样单变量序列模型 不规则采样序列的频谱 VCZAR 模型选择建议 定期采样双变量序列模型 不规则采样双变量序列模型 连接图形、谱和 VZAR 方法 主题概述 部分相关性图 因果响应的谱估计结构 VZAR、SVZAR 进一步可能的发展 参考书目 主题索引 作者索引
Introduction and overview Examples of time series Dependence within and between time series Some of the challenges of time series modeling Feedback and cycles Challenges of high frequency sampling Causal modeling and structure Some practical considerations Lagged regression and autoregressive models Stationary discrete time series and correlation Autoregressive approximation of time series Multi-step autoregressive model prediction Examples of autoregressive model approximation The multivariate autoregressive model Autoregressions for high lead time prediction Model impulse response functions The covariances of the VAR model Partial correlations of the VAR model Inverse covariance of the VAR model Autoregressive Moving Average models State space representation of VAR models Projection using the covariance matrix Lagged response functions of the VAR model Spectral analysis of dependent series Harmonic components of time series Cycles and lags Cycles and stationarity The spectrum and cross-spectra of time series Dependence between harmonic components Bivariate and multivariate spectral properties Estimation of spectral properties Sample covariances and smoothed spectrum Tapering and pre-whitening Practical examples of spectral analysis Harmonic contrasts in large samples The estimation of vector autoregressions Methods of estimation The spectrum of a VAR model Yule-Walker estimation of the VAR(p) model Estimation of the VAR(p) by lagged regression Maximum likelihood estimation, MLE VAR models with exogenous variables, VARX The Whittle likelihood of a time series model Graphical modeling of structural VARs The structural VAR, SVAR The directed acyclic graph, DAG The conditional independence graph, CIG Interpretation of CIGs Properties of CIGs Estimation and selection of DAGs Building a structural VAR, SVAR Properties of partial correlation graphs Simultaneous equation modeling An SVAR model for the Pig market: the innovations A full SVAR model of the Pig market series VZAR: an extension of the VAR model Discounting the past The generalized shift operator The VZAR model Properties of the VZAR model Approximating a process by the VZAR model Yule-Walker fitting of the VZAR Regression fitting of the VZAR Maximum likelihood fitting of the VZAR VZAR model assessment Continuous time VZAR models Continuous time series Continuous time autoregression and the CAR(1) The CAR(p) model The continuous time generalized shift The continuous time VZAR model, VCZAR Properties of the VCZAR model Approximating a continuous process by a VCZAR Yule-Walker fitting of the VCZAR model Regression and ML estimation of the VCZAR Irregularly sampled series Modeling of irregularly sampled series The likelihood from irregularly sampled data Irregularly sampled univariate series models The spectrum of irregularly sampled series Recommendations on VCZAR model selection A model of regularly sampled bivariate series A model of irregularly sampled bivariate series Linking graphical, spectral and VZAR methods Outline of topics Partial coherency graphs Spectral estimation of causal responses The structural VZAR, SVZAR Further possible developments Bibliography Subject Index Author Index