Fill in historic ndvi data to the complete timeseries being fit
Usage
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)
