Time Series Forecasting and Interpolation
Interpolating gaps in light curves and forecasting future values
Here we illustrate how we can use Gaussian Process modeling to interpolate missing data and forecast time series. The basic idea is to first model the power spectral density of the observed data (learn from the data), and then by use the model, conditioned on the observed data, to fill...
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