学习经典分解:时间序列分析方法教程

IF 0.4 4区 数学 Q4 MATHEMATICS
Marco Aurélio Carino Bouzada
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引用次数: 7

摘要

这项工作提出了一个教程,教授一种定量的预测方法,称为经典分解,在商业中用于预测具有不同解释性成分的时间序列的未来行为。一个简短的文献综述是发展的关系,已经知道和广泛的理论方面的方法。然后,教程本身呈现出来,它由文本(完整)和电子表格(带有屏幕和图形作为说明)组成。该教程可供需要学习经典分解的学生,研究人员和管理人员使用,并且可以实现纯理论方法和非常技术的方法实现指南之间的中点。本研究旨在鼓励学生积极参与学习过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Aprendendo Decomposição Clássica: Tutorial para um Método de Análise de Séries Temporais
This work presents a tutorial to teach a quantitative methodology for forecasting known as Classical Decomposition, used in business to predict the future behavior of time series with different explicative components. A brief Literature Review was developed in relation to the already known and widespread theoretical aspects of the methodology. Then, the tutorial itself is presented which is composed of a text (in its entirety) and a spreadsheet (with screens and graphics for illustration). The tutorial can be used by students, researchers and managers who need to learn Classical Decomposition and can achieve the midpoint between a purely theoretical approach and a very technical guide for implementation of the method. Through its format, this study aims to encourage students to actively participate in the learning process.
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来源期刊
Theory and Applications of Categories
Theory and Applications of Categories MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
1.30
自引率
0.00%
发文量
0
期刊介绍: The journal Theory and Applications of Categories will disseminate articles that significantly advance the study of categorical algebra or methods, or that make significant new contributions to mathematical science using categorical methods. The scope of the journal includes: all areas of pure category theory, including higher dimensional categories; applications of category theory to algebra, geometry and topology and other areas of mathematics; applications of category theory to computer science, physics and other mathematical sciences; contributions to scientific knowledge that make use of categorical methods.
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