June 2020
Beginner to intermediate
522 pages
9h 6m
Chinese
Content preview from R 语言经典实例（原书第 2 版）
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时间序列分析
｜
439
请注意，滞后 0 阶的相关性为
-
0.24，这是变量之间的简单相关系数：
cor(b, c)
#> [1] -0.24
更为有趣的是滞后 1 阶、5 阶和 8 阶的相关性，这在统计上是显著的。显然，债券和商
品的日常价格存在一些“联动反应”，因为明天的变化与今天的变化是相关的。发现这
种关系对短期预测者很有用，例如市场分析师和债券交易者。
14.17 剔除时间序列的趋势
14.17.1 问题
剔除时间序列数据包含的趋势。
14.17.2 解决方案
使用线性回归来标识趋势成分，然后从原始时间序列中减去趋势成分。以下代码显示如
何去除 zoo 对象 ts 的趋势成分，并将结果放在 detr 中：
m <- lm(coredata(ts) ~ index(ts))
detr <- zoo(resid(m), index(ts))
14.17.3 讨论
有的时间序列数据包含趋势，这意味着它随着时间的推移逐渐向上或向下倾斜。假设我
们的时间序列对象（在本例中是一个 zoo 对象）yield 包含一个趋势，如图 14-10 所示。
IL Corn Yield (bu/ac)
200
175
150
125
100
yield
1990 2000 2010
Index
图 14-10：带趋势的时间序列
440
｜
第
14
章
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