outliers and unusual observations

[mnbvcxz]

Hi everyone,

in what function can I examine the importance of outliers and unusual observations in the time series?

I would like to prepare my script in the following way:

1. when time series have outliers with big impact then I use tsclean() or BoxCox()
2. in different situation I don't want to use mentioned data transformations

but I don't know how can I check the importance of outliers observations...

thanks for any help

[andresrcs]

Assuming that by unusual observations you mean leverage points you can asses its influence by inspecting Cook’s distance, but you should only worry about leverage points which are also outliers.

If you need more specific help please provide a minimal REPRoducible EXample (reprex) ilustrating your issue. A reprex makes it much easier for others to understand your issue and figure out how to help.

If you've never heard of a reprex before, you might want to start by reading this FAQ:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…