A Maple package for improved global mapping forecast

Abstract
We present a Maple implementation of the well known global approach to time series analysis and some further developments designed to improve the computational efficiency of the forecasting capabilities of the approach. This global approach can be summarized as being a reconstruction of the phase space, based on a time ordered series of data obtained from the system. After that, using the reconstructed vectors, a portion of this space is used to produce a mapping, a polynomial fitting, throug...

Title of program: TimeS
Catalogue Id: AERW_v1_0

Nature of problem
Time series analysis and improving forecast capability.

Versions of this program held in the CPC repository in Mendeley Data
AERW_v1_0; TimeS; 10.1016/j.cpc.2013.12.001

This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)

摘要
本文提出了经典时序分析全局方法的Maple实现，并针对提升该方法的计算效率与预测性能开展了进一步拓展研究。该全局方法的核心流程可概括为：基于从目标系统获取的时序数据集重构相空间；随后利用重构得到的相空间向量，选取该空间的部分区域构建映射关系，即通过多项式拟合……

程序名称：TimeS
目录编号：AERW_v1_0

问题属性
时序分析与预测性能优化。

Mendeley Data收录的CPC程序库版本
AERW_v1_0; TimeS; 10.1016/j.cpc.2013.12.001

本程序源自贝尔法斯特女王大学维护的CPC程序库（1969-2019）