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
Exercise instructions
Use last observation carried forward to impute missing values in
monthly_test_scores
; save this asmonthly_scores_locf
.Complete the first
autoplot()
to generate a plot of the originalmonthly_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 ofmonthly_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(___) +
___