Fill in historic ndvi data to the complete timeseries being fit

fill_missing_ndvi(ndvi, level, last_time, moons = NULL)

Arguments

ndvi: ndvi data
level: specify "monthly" or "newmoon"
last_time: the last time step to have been completed
moons: moon data (required if level = "newmoons" and forecasts are needed)

Value

a data.frame with time and ndvi values

Details

missing values during the time series are replaced using na.interp, missing values at the end of the time series are forecast using auto.arima with seasonality (using Fourier transform)