论文标题
对不断变化的极端依赖结构的统计推断
Statistical Inference on a Changing Extremal Dependence Structure
论文作者
论文摘要
我们分析了独立的极端价值依赖性，不一定是分布的多元定期变化的随机向量。更具体地说，我们在某个时间点和随着时间的时间积分的光谱度量局部提出了频谱度量的估计量。这些估计量的均匀正态性在适当的非参数平滑度和规律性假设下被证明。然后，我们使用集成光谱度量的过程收敛来设计一致的测试，以证明光谱度量不会随时间变化而变化。这些测试的有限样本性能在蒙特卡洛模拟中研究。
We analyze the extreme value dependence of independent, not necessarily identically distributed multivariate regularly varying random vectors. More specifically, we propose estimators of the spectral measure locally at some time point and of the spectral measures integrated over time. The uniform asymptotic normality of these estimators is proved under suitable nonparametric smoothness and regularity assumptions. We then use the process convergence of the integrated spectral measure to devise consistent tests for the null hypothesis that the spectral measure does not change over time. The finite sample performance of these tests is investigated in Monte Carlo simulations.
