问题描述
在R中检测业务销售数据中的异常值（意味着可能存在趋势和季节性）需要采取哪些步骤？
What are the steps needed to detect outliers in business sales data (which means there might be trends and seasonality) in R?
我了解了ACF，PACF ，残差，ARIMA模型（基本上是时间序列分析和建模）。我可以利用这些知识来帮助识别异常值吗？
I have learnt about ACF, PACF, residual, ARIMA model (basically, time series analysis and modelling). Can I use this knowledge to help me identify outliers?
是否还可以要求R指出哪个数据点是异常值？
Is it also possible to ask R to pinpoint which point of data is outlier?
非常感谢。
推荐答案
您可能会看到R中提供的以下软件包。
You may have a look at the following packages available in R.
R包实现了过程用于检测时间序列中的异常值。包装随附的文档中提供了有关过程和实现的说明。您可能还会看到。
The R package tsoutliers implements the Chen and Liu procedure for detection of outliers in time series. A description of the procedure and the implementation is given in the documentation attached to the package. You may also see this post.
这篇关于R中时间序列数据的异常检测的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！