ARIMIA and Kalman Filter Gap Fill

Fill gaps in a timeseries by fitting an ARIMA model and applying a Kalman filter.

gapfill_kalman(x, mask = is.na(x), ...)

Arguments

x	A vector of data with missing values.
mask	A logical mask that identifies a subgroup of x to compute fill values for. Useful when a subset of quality-assured data is available. Default action is to only fill NA values.
...	Additional arguments to forecast::auto.arima().

Value

The original vector x with missing values imputed.