Clean Speed Outliers in a Dataset

The clean_speed function identifies and removes speed outliers from a given dataset based on the Median Absolute Deviation (MAD). The function can identify both "fast" and "slow" outliers, depending on the parameter settings. It prints the number of identified outliers, initial number of observations, final number of observations after removing outliers, and the number of observations removed.

Usage

clean_speed(data, duration_var, remove_slow = FALSE)

Arguments

data

A dataset where speed outliers need to be identified and removed.

duration_var

The variable in the dataset used to identify outliers.

remove_slow

A logical value to decide if slow outliers should be removed (default is FALSE).

Value

A dataset where speed outliers have been removed.

References

Remember to add reference here.

Examples

if (FALSE) {
# Generate some data
df <- data.frame(
  duration = c(1, 2, 3, 4, 5, 6, 1000, 2000, 50000, -50, -200),
  other_var = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
)

# Remove speed outliers from the data
clean_data <- clean_speed(df, duration_var = "duration", remove_slow = TRUE)
}