Abstract
Verifiable conditions are given for the validity of formal Edgeworth expansions for the distribution of sums $X_1 + \cdots + X_n$, where $X_i = F(Z_i, \ldots, Z_{i + p - 1})$ and $Z_1, Z_2, \ldots$ is a strict sense stationary sequence that can be written as $Z_j = g(\varepsilon_{j - k}: k \geq 0)$ with an $\operatorname{iid}$ sequence $(\varepsilon_i)$ 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.
Citation
F. Gotze. C. Hipp. "Asymptotic Distribution of Statistics in Time Series." Ann. Statist. 22 (4) 2062 - 2088, December, 1994. https://doi.org/10.1214/aos/1176325772
Information