@incollection{epos1886,
       booktitle = {Time Series Analysis: Forecasting and Control},
           title = {Autocorrelation Function and Spectrum of Stationary Processes},
          author = {George E. P. Box and Gwilym M. Jenkins and Gregory C. Reinsel and Greta M. Ljung},
       publisher = {Wiley},
           pages = {21--46},
             url = {https://episodesplatform.eu/eprints/1886/},
        abstract = {2. Autocorrelation Function and Spectrum of Stationary Processes 21
2.1 Autocorrelation Properties of Stationary Models, 21
2.1.1 Time Series and Stochastic Processes, 21
2.1.2 Stationary Stochastic Processes, 24
2.1.3 Positive Definiteness and the Autocovariance Matrix, 26
2.1.4 Autocovariance and Autocorrelation Functions, 29
2.1.5 Estimation of Autocovariance and Autocorrelation Functions, 30
2.1.6 Standard Errors of Autocorrelation Estimates, 31
2.2 Spectral Properties of Stationary Models, 34
2.2.1 Periodogram of a Time Series, 34
2.2.2 Analysis of Variance, 35
2.2.3 Spectrum and Spectral Density Function, 36
2.2.4 Simple Examples of Autocorrelation and Spectral Density
Functions, 40
2.2.5 Advantages and Disadvantages of the Autocorrelation and Spectral
Density Functions, 43
Appendix A2.1 Link Between the Sample Spectrum and Autocovariance
Function Estimate, 43
Exercises, 44}
}