Time Series and Spectral Analysis
Lyle David Broemeling · 2019
This chapter introduces the reader to the Bayesian approach of estimating the spectral density of the basic times series model, including the autoregressive, the moving average, and the autoregressive moving averages models. The chapter begins with the fundamental ideas for defining the spectral density function. First, the general harmonic model containing sine and cosine functions is described for representing a seasonal time series. Next the unit of measurement for frequency is defined which allows one to give a general definition of the spectral density. R plays an important role in generating time series and computing the spectral density.