Removing trends in variability via the logarithmic transformation

The logarithmic function log() is a data transformation that can be applied to positively valued time series data. It slightly shrinks observations that are greater than one towards zero, while greatly shrinking very large observations. This property can stabilize variability when a series exhibits increasing variability over time. It may also be used to linearize a rapid growth pattern over time.

The time series rapid_growth has already been loaded, and is shown in the figure on the right. Note the vertical range of the data.

This exercise is part of the course

Time Series Analysis in R

View Course

Exercise instructions

Apply the log() function to rapid_growth, saving the result as linear_growth.
Use ts.plot() to show the transformed series linear_growth and note the condensed vertical range of the transformed data.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Log rapid_growth
linear_growth <-
  
# Plot linear_growth using ts.plot()

Edit and Run Code