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Last observation carried forward (LOCF)

Another important imputation method is Last observation carried forward, or LOCF. This method works by filling in missing values with the most recent non-NA value that came before it.

In this exercise, you will impute a time series of a student's monthly examination scores, called monthly_test_scores. This dataset, along with the ggplot2 and zoo packages, are available to you.

This exercise is part of the course

Manipulating Time Series Data in R

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Exercise instructions

  • Use last observation carried forward to impute missing values in monthly_test_scores; save this as monthly_scores_locf.

  • Complete the first autoplot() to generate a plot of the original monthly_test_scores time series.

  • Autoplot monthly_scores_locf with the 'minimal' theme, and the y-axis label "Examination Score (LOCF)".

  • Compare the plot of monthly_scores_locf with the plot of monthly_test_scores by switching between the plots.

Hands-on interactive exercise

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

# Impute using last observation carried forward
___ <- ___

# Create a plot of the original time series 
autoplot(___) + 
  theme_minimal() + 
  labs(y = "Examination Score")

# Autoplot with theme and axis title and compare to the above plot
autoplot(___) + 
  ___
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