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R 语言经典实例(原书第 2 版)
book

R 语言经典实例(原书第 2 版)

by J.D. Long, Paul Teetor
June 2020
Beginner to intermediate
522 pages
9h 6m
Chinese
China Machine Press
Content preview from R 语言经典实例(原书第 2 版)
448
14
Residuals from ARIMA (1, 1, 1) (0, 0, 1) [4]
1
0
-
1
ACF
0.4
0.2
0.0
-
0.2
2000 2005 2010
4 8 12 16
count
15
10
5
0
-
2
-
1 0 1
Lag residuals
14-15:残差图:问题模型
以上都是基本的诊断,但它们是模型诊断的一个良好起点。找到一本关于 ARIMA 模型
的好书并执行建议的诊断检验,然后再确定模型是合理的。其他对残差进行的诊断可
包括:
正态性检验
Q-Q
拟合值的散点图
14.21 ARIMA 模型进行预测
14.21.1 问题
已经使用 forecast 包对时间序列构建 ARIMA 模型。需要预测序列未来的观测值。
14.21.2 解决方案
将模型保存在对象中,然后将函数 forecast 应用于对象。此示例从 14.19 节中保存模
型并预测接下来的八个观测值:
m <- arima(euretail, order = c(0, 1, 3), seasonal = c(0, 1, 1),
fixed = c(0, NA, NA, NA))
forecast(m)
#> Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
#> 2012 Q1 95.1 94.6 95.6 94.3 95.9
#> 2012 Q2 95.2 94.5 95.9 94.1 96.3
#> 2012 Q3 95.2 94.2 96.3 93.7 ...
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Publisher Resources

ISBN: 9787111656814