Asymptotic Distribution of Statistics in Time Series
Asymptotic Distribution of Statistics in Time Series
复制标题
时间序列统计量的渐近分布
DOI：
10.1214/aos/1176325772
复制
发表时间：
1994
影响因子：
4.5
通讯作者：
C. Hipp
中科院分区：
文献类型：
--
作者：
F. Götze;C. Hipp
给出了和x1 +…分布的形式Edgeworth展开式的有效性的证明条件。+ xn，其中xi = F（zi，…）， zi + p−1)和z1， z2，…是一个严格意义上的平稳序列，可以写成zj = g(E j−k: k≥0)，具有创新的iid序列（E i）。这些模型包括ARMA过程的非线性函数（zi）以及某些非线性AR过程。结果适用于（非线性）时间序列模型中的许多统计量
Veritable conditions are given for the validity of formal Edgeworth expansions for the distribution of sums X 1 +... + X n , where X i = F(Z i ,..., Z i + p − 1) and Z 1 ,Z 2 ,... is a strict sense stationary sequence that can be written as Z j = g(E j − k : k ≥ 0) with an iid sequence (E i ) of innovations. These models include nonlinear functions of ARMA processes (Z i ) as well as certain nonlinear AR processes. The results apply to many statistics in (nonlinear) time series models