适用于Matlab的SSM
The SSM Toolbox for Matlab
摘要：
状态空间模型（SSM）是一个MATLAB 7.0软件工具箱，用于通过状态空间方法进行时间序列分析。该软件具有完全交互式的模型构建和组合功能，支持单变量和多变量模型，复杂的时变（动态）模型，非高斯模型以及各种标准模型，如ARIMA和结构时间序列模型。该软件包括卡尔曼滤波和平滑、模拟平滑、似然估计、参数估计、信号提取和预测的标准功能，并结合了滤波器和平滑器的精确初始化，支持缺失观测和具有共同分析结构的多个时间序列输入。该软件还包括TRAMO模型选择和ARIMA模型的Hillmer-Tiao分解的实现。该软件将提供一个在MATLAB平台上进行时间序列分析的通用工具箱，使用户能够利用其现成的图形绘制和通用矩阵计算能力。
英文摘要：
State Space Models (SSM) is a MATLAB 7.0 software toolbox for doing time series analysis by state space methods. The software features fully interactive construction and combination of models, with support for univariate and multivariate models, complex time-varying (dynamic) models, non-Gaussian models, and various standard models such as ARIMA and structural time-series models. The software includes standard functions for Kalman filtering and smoothing, simulation smoothing, likelihood evaluation, parameter estimation, signal extraction and forecasting, with incorporation of exact initialization for filters and smoothers, and support for missing observations and multiple time series input with common analysis structure. The software also includes implementations of TRAMO model selection and Hillmer-Tiao decomposition for ARIMA models. The software will provide a general toolbox for doing time series analysis on the MATLAB platform, allowing users to take advantage of its readily available graph plotting and general matrix computation capabilities.
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。
