无烧失期的VARMA时间序列模拟
Burn-in-Free Simulation of VARMA Time Series
- University of Iceland（冰岛大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
研究开发了无需烧失期的VARMA时间序列模拟软件包Varmapack，支持多语言接口及多种计算功能，性能远超同类软件，为时间序列模拟提供高效开源工具。
AI中文摘要：
Varmapack是一款用于高效、精确模拟VARMA时间序列的软件包，无需烧失期。对于平稳模型，Varmapack可从其联合平稳分布生成初始状态和新息；用户也可自行提供初始状态，此时新息将从其条件分布生成。核心C库提供了对R、Python和Matlab的接口，还支持VARMAX模拟，以及自协方差、相关性、谱半径和脉冲响应的计算。Varmapack会自动在向量-Yule-Walker方法和状态空间方法中选择用于协方差计算，并使用3级BLAS操作高效生成多个重复样本。在多个平台上的基准测试显示，相较于现有模拟软件，其性能提升显著，针对所考察的软件包和模型，提升幅度从数倍到超过三个数量级不等。Varmapack为开源软件，可通过GitHub公开获取。
英文摘要：
Varmapack is a software package for efficient, exact simulation of VARMA time series without a burn-in period. For stationary models, Varmapack can generate initial states and innovations from their joint stationary distribution. Alternatively, the user can supply initial states, in which case innovations are generated from their conditional distribution. The core C library has interfaces to R, Python, and Matlab. It also offers VARMAX simulation and computation of autocovariances and correlations, spectral radii, and impulse responses. Varmapack automatically selects between vector-Yule-Walker and state-space methods for covariance computation and uses level-3 BLAS operations for efficient generation of multiple replicates. Benchmarks on several platforms show substantial performance gains over existing simulation software, ranging from several-fold to more than three orders of magnitude for the packages and models considered. Varmapack is open source and publicly available through GitHub.
