gmwm R软件包：从状态空间模型到鲁棒性的时间序列分析综合工具
The gmwm R package: a comprehensive tool for time series analysis from state-space models to robustness
摘要：
用于对时间序列模型进行推断的gmwm R包主要基于称为小波方差的量，该量来自于对时间序列的小波分解。这一数量提供了一种手段来总结和图形表示时间序列的特点，以确定可能的模式。并将其作为矩条件，通过广义小波矩方法进行模型估计。基于后一种方法，该软件包不仅提供了一种替代方法来估计经典的ARMA模型，但也提供了一个通用的框架，稳健估计的许多时间序列模型，以及快速和有效的估计许多线性状态空间模型。
英文摘要：
The gmwm R package for inference on time series models is mainly based on the quantity called wavelet variance which is derived from a wavelet decomposition of a time series. This quantity provides a means to summarize and graphically represent the features of time series in order to identify possible models. Moreover, it is used as a moment condition for model estimation through the generalized method of wavelet moments. Based on the latter method, this package not only provides an alternative method to estimate classical ARMA models but also delivers a general framework for the robust estimation of many time series models as well as a quick and efficient estimation of many linear state-space models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
