Seasonal subseries plot
Seasonal subseries plots are a tool for detecting seasonality in a time series. This plot allows one to detect both between-group and within-group patterns. This plot is only useful if the period of the seasonality is already known. In many cases, this will in fact be known. For example, monthly data typically has a period of 12. If the period is not known, an autocorrelation plot or spectral plot can be used to determine it. If there is a large number of observations, then a box plot may be preferable.
Definition
Seasonal subseries plots are formed by
- Vertical axis: response variable
- Horizontal axis: time ordered by season. For example, with monthly data, all the January values are plotted (in chronological order), then all the February values, and so on.
In addition, a reference line is drawn at the group means.
The analyst must specify the length of the seasonal pattern before generating this plot. In most cases, the analyst will know this from the context of the problem and data collection.
Importance
It is important to know when analyzing a time series if there is a significant seasonality effect. The seasonal subseries plot is an excellent tool for determining if there is a seasonal pattern. The seasonal subseries plot can provide answers to the following questions:
- Do the data exhibit a seasonal pattern?
- What is the nature of the seasonality?
- Is there a within-group pattern (e.g., do January and July exhibit similar patterns)?
- Are there any outliers once seasonality has been accounted for?
Related techniques
- Autocorrelation plot
- Box plot
- Recurrence plot
- Run sequence plot
Software
Seasonal subseries plots are implemented in the R function monthplot().
References
- Cleveland, William (1993). Visualizing Data. Hobart Press.
External links
This article incorporates public domain material from websites or documents of the National Institute of Standards and Technology.