On the Bartels Technique for Time-Series Analysis, and its Relation to the Analysis of Variance
Bartels 时间序列分析技术及其与方差分析的关系AI 解读 ↓
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Bartels 时间序列分析技术及其与方差分析的关系
- 研究问题
- 连续观测存在序列相关时，如何缓解常规统计技术的适用困难，物理学中的 Bartels 技术能提供什么帮助？
- 方法与思路
- 作者介绍物理学中用于类似相关问题的一种近似、直观技术，希望推动统计应用与进一步审查；摘要未展示操作步骤。
- 材料陈述的贡献
- 摘要所述贡献是把相关领域的一项技术引入统计讨论，并指出其潜在用途；与方差分析的具体关系仅见于题名。
- 阅读关注点
- 应核对 Bartels 技术的计算程序、近似依据、适用的相关结构，以及题名所称与方差分析之间的具体联系。
- 阅读边界
- 仅据版本未注明的索引摘要；技术被描述为近似直观方法，材料未说明有效性条件、比较结果或刊本变化。
原文摘要
IT HAS long been recognized that there is difficulty in applying the usual statistical techniques when there is correlation between successive items in any given sample. This trouble arises in many different fields: in economic time series the index number for any one day, month, or year is dependent on that of the preceding time unit. In sociology the number of strikes in progress at any one time is dependent on the number at some immediately preceding time. In agricultural experiments the yield of any plot will be high or low with the fertility of the adjacent region. This characteristic is known by various names, among statisticians as serial correlation, among physicists as nachwirkung or persistence. Various devices are used by statisticians to circumvent it, but the problem is by no means solved. For this reason it may not be amiss to bring to the attention of statisticians an approximate intuitive device used on similar problems by physicists, with the hope not only that the method in its present form might prove of some value to statisticians, but also that they may be stimulated into a more critical study of the technique.