Skip to main content

IE 692: Applied Time Series Analysis

Contents

Harmonic Analysis of stationary random processes; spectral representation of the process; stationary process; stationary processes with spectral densities.

Linear extrapolation, filtering and interpolation of stationary processes.

Stationary moving average autoregressive ARMA and ARIMA process; estimation of parameters; verification identification, Maximum and mean likelihood estimation. Box Jenkins modeling application in economics and business, Consistent estimation of autospectrum and cross spectrum. Choice of spectral window. Use of Digital filters. Kalman filter, FFT

Transfer function model estimation; Closed loop models.

Alternative to box Jenkins approach , ARUA models.

References

  • Yu. A. Rozano (1967), Stationary Random Processes, Holden-Day.
  • G.M. Jenkins and D.G. Watts (1968), Spectral Analysis and its Applications, Holden-Day
  • G.E.P. Box and G.M. Jenkins (1970), Time Series Analysis, Forecasting and Control, Holden Day.
  • O.D Anderson (1978), The Statistical analysis of Time Series Wiley.
  • O.D. Anderson and M.R. Perryman Eds. (1981), Time Series Analysis, North-Holland.