The project demonstrates Spectral Analysis and Forecasting performed on Time Series obtained from Astronomical Observations
The project employs the use of various Periodogram-based techniques like Fourier Transform, Lomb - Scargle Method, to estimate the Power Spectral Density at various frequencies.
The accurate forecasting of the data was done by estimating the various parameters of an ARIMA model, by the analysis of the Auto-Correlation Function (ACF) and the Partial Auto-Correlation Function (PACF) of the data.
The above-mentioned methods were employed on both evenly-sampled data (LIGO) as well as unevenly-sampled data (LINEAR)