`modify_short_drift()` corrects short-term drifts by adjusting the 5th and 95th percentiles of the drifted time series to those of the reference time series.
Usage
modify_short_drift(
vctr_time,
vctr_target,
vctr_time_drft_head,
vctr_time_drft_tail,
n_day_ref = 3,
label_err = -9999
)Arguments
- vctr_time
A timestamp vector of class POSIXct or POSIXt. The timestamps must be equally spaced and arranged chronologically.
- vctr_target
A vector of a targeted time series to be checked. The length of the time series must be the same as that of `vctr_time`.
- vctr_time_drft_head
A timestamp vector of class POSIXct or POSIXt, indicating when each drift starts.
- vctr_time_drft_tail
A timestamp vector of class POSIXct or POSIXt, indicating when each drift ends. The length of the time series must be the same as that of `vctr_time_drft_head`.
- n_day_ref
A positive integer representing the number of days to be referenced before and after the anomaly period. Default is 3 (days).
- label_err
A numeric value representing a missing value in the input vector(s). Default is -9999.
Value
A vector of the drift-corrected time series. The length of the time series is the same as the input time series.
Details
The short-term drift correction is to correct sudden changes in the average in the time series over a short period (hours to days) specified by `vctr_time_drft_head` and `vctr_time_drft_tail`. Multiple short-term drifts can be corrected at once using this function.This procedure uses a reference period, which is defined to consist of the three days (default) before and after the occurrence of the anomaly. Then, the anomalous time series is standardized so that the 5th and 95th percentile values of the anomalous and reference (non-anomalous) time series match over this period. These percentile values are used instead of the maximum and minimum values to ensure robustness against possible outliers in the original or reference time series.
Examples
## Load data
data(dt_noisy)
time <- dt_noisy$time[11931:12891]
target <- dt_noisy$dt[11931:12891]
time_drft_head <- time[1]
time_drft_tail <- time[148]
## Correct a short-term drift
result <-
modify_short_drift(vctr_time = time, vctr_target = target,
vctr_time_drft_head = time_drft_head,
vctr_time_drft_tail = time_drft_tail)