This paper proposes a novel multivariate time series model named Copula-linked univariate D-vines (CuDvine), which enables the simultaneous copula-based modeling of both temporal and cross-sectional dependence for multivariate time series. To construct CuDvine, we first build a semiparametric univariate D-vine time series model (uDvine) based on a D-vine. The uDvine generalizes the existing first-order copula-based Markov chain models to Markov chains of an arbitrary-order. Building upon uDvine, we construct CuDvine by linking multiple uDvines via a parametric copula. As a simple and tractable model, CuDvine provides flexible models for marginal behavior and temporal dependence of time series, and can also incorporate sophisticated cross-sectional dependence such as time-varying and spatio-temporal dependence for high-dimensional applications. Robust and computationally efficient procedures, including a sequential model selection method and a two-stage MLE, are proposed for model estimation and inference, and their statistical properties are investigated. Numerical experiments are conducted to demonstrate the flexibility of CuDvine, and to examine the performance of the sequential model selection procedure and the two-stage MLE. Real data applications on the Australian electricity price data demonstrate the superior performance of CuDvine to traditional multivariate time series models.
翻译:本文提出一个新的多变时间序列模型,名为Copula-联连的单一亚特D-vine(CuDvine),它可以同时以相交式模式建库德维内,同时以相交式模式建构多变时间序列的时间依赖度和跨部门依赖性。为了建设CuDvine,我们首先在Dvine的基础上建立一个半参数性单异度D-vine时间序列模型(uDvine)。uDvine将现有的以一阶相联的相联式单立式连锁模式(markovov)概括到一个任意秩序的Markov连锁。在uDvine的基础上,我们通过一个准分立式 Codvine 将多个uDvines同时建库德维尼德维尼(CuDvine)同时建模。CuDvine作为一个简单和可拉动的模式,为边际行为和时间序列的时依赖性模型提供了灵活的模型,还可以包含复杂的跨段依赖性模型,例如时间变换和高度应用程序。 Robust和计算高效程序,包括顺序模型选择方法和双级MLEE,这是为模型,用来进行模型,用于模型和Cufreal-Cufreal-Ce-Cufreal数据的模拟的模拟的模拟的模拟的测试,以显示和Cual-de-Cu-Cu-de-de-de-de-Cu-de-de-de-de-de-de-de-de-de-de-de-de-deal-de-de-deal-deal-de-de-de-deal-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-de-