Forecasting Process Details


References

  • Akaike, H. (1974), “A New Look at the Statistical Model Identification,” IEEE Transactions on Automatic Control, AC-19, 716–723.

  • Aldrin, M. and Damsleth, E. (1989), “Forecasting Non-seasonal Time Series with Missing Observations,” Journal of Forecasting, 8, 97–116.

  • Anderson, T. W. (1971), The Statistical Analysis of Time Series, New York: John Wiley & Sons.

  • Ansley, C. F. (1979), “An Algorithm for the Exact Likelihood of a Mixed Autoregressive–Moving Average Process,” Biometrika, 66, 59–65.

  • Ansley, C. F. and Newbold, P. (1980), “Finite Sample Properties of Estimators for Autoregressive Moving-Average Models,” Journal of Econometrics, 13, 159–183.

  • Archibald, B. C. (1990), “Parameter Space of the Holt-Winters’ Model,” International Journal of Forecasting, 6, 199–209.

  • Bartolomei, S. M. and Sweet, A. L. (1989), “A Note on the Comparison of Exponential Smoothing Methods for Forecasting Seasonal Series,” International Journal of Forecasting, 5, 111–116.

  • Bhansali, R. J. (1980), “Autoregressive and Window Estimates of the Inverse Correlation Function,” Biometrika, 67, 551–566.

  • Bowerman, B. L. and O’Connell, R. T. (1979), Time Series and Forecasting: An Applied Approach, North Scituate, MA: Duxbury Press.

  • Box, G. E. P. and Cox, D. R. (1964), “An Analysis of Transformations,” Journal of the Royal Statistical Society, Series B, 26, 211–234.

  • Box, G. E. P. and Jenkins, G. M. (1976), Time Series Analysis: Forecasting and Control, Rev. Edition, San Francisco: Holden-Day.

  • Box, G. E. P. and Tiao, G. C. (1975), “Intervention Analysis with Applications to Economic and Environmental Problems,” Journal of the American Statistical Association, 70, 70–79.

  • Brocklebank, J. C. and Dickey, D. A. (1986), SAS System for Forecasting Time Series, 1986 Edition, Cary, NC: SAS Institute Inc.

  • Brown, R. G. (1962), Smoothing, Forecasting, and Prediction of Discrete Time Series, New York: Prentice-Hall.

  • Brown, R. G. and Meyer, R. F. (1961), “The Fundamental Theorem of Exponential Smoothing,” Operations Research, 9, 673–685.

  • Chatfield, C. (1978), “The Holt-Winters Forecasting Procedure,” Applied Statistics, 27, 264–279.

  • Chatfield, C. and Prothero, D. L. (1973), “Box-Jenkins Seasonal Forecasting: Problems in a Case Study,” Journal of the Royal Statistical Society, Series A, 136, 295–315.

  • Chatfield, C. and Yar, M. (1988), “Holt-Winters Forecasting: Some Practical Issues,” The Statistician, 37, 129–140.

  • Chatfield, C. and Yar, M. (1991), “Prediction Intervals for Multiplicative Holt-Winters,” International Journal of Forecasting, 7, 31–37.

  • Cogger, K. O. (1974), “The Optimality of General-Order Exponential Smoothing,” Operations Research, 22, 858–867.

  • Cox, D. R. (1961), “Prediction by Exponentially Weighted Moving Averages and Related Methods,” Journal of the Royal Statistical Society, Series B, 23, 414–422.

  • Davidson, J. (1981), “Problems with the Estimation of Moving Average Models,” Journal of Econometrics, 16, 295.

  • Dickey, D. A. and Fuller, W. A. (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root,” Journal of the American Statistical Association, 74, 427–431.

  • Dickey, D. A., Hasza, D. P., and Fuller, W. A. (1984), “Testing for Unit Roots in Seasonal Time Series,” Journal of the American Statistical Association, 79, 355–367.

  • Fair, R. C. (1986), “Evaluating the Predictive Accuracy of Models,” in Z. Griliches and M. D. Intriligator, eds., Handbook of Econometrics, volume 3, New York: North-Holland.

  • Fildes, R. (1979), “Quantitative Forecasting—the State of the Art: Extrapolative Models,” Journal of Operational Research Society, 30, 691–710.

  • Fuller, W. A. (1976), Introduction to Statistical Time Series, New York: John Wiley & Sons.

  • Gardner, E. S., Jr. (1984), “The Strange Case of the Lagging Forecasts,” Interfaces, 14, 47–50.

  • Gardner, E. S., Jr. (1985), “Exponential Smoothing: The State of the Art,” Journal of Forecasting, 4, 1–38.

  • Granger, C. W. J. and Newbold, P. (1977), Forecasting Economic Time Series, New York: Academic Press.

  • Greene, W. H. (1993), Econometric Analysis, 2nd Edition, New York: Macmillan.

  • Hamilton, J. D. (1994), Time Series Analysis, Princeton, NJ: Princeton University Press.

  • Harvey, A. C. (1981), Time Series Models, New York: John Wiley & Sons.

  • Harvey, A. C. (1984), “A Unified View of Statistical Forecasting Procedures,” Journal of Forecasting, 3, 245–275.

  • Hopewood, W. S., McKeown, J. C., and Newbold, P. (1984), “Time Series Forecasting Models Involving Power Transformations,” Journal of Forecasting, 3, 57–61.

  • Jones, R. H. (1980), “Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations,” Technometrics, 22, 389–396.

  • Judge, G. G., Griffiths, W. E., Hill, R. C., and Lee, T.-C. (1980), The Theory and Practice of Econometrics, New York: John Wiley & Sons.

  • Ledolter, J. and Abraham, B. (1984), “Some Comments on the Initialization of Exponential Smoothing,” Journal of Forecasting, 3, 79–84.

  • Ljung, G. M. and Box, G. E. P. (1978), “On a Measure of Lack of Fit in Time Series Models,” Biometrika, 65, 297–303.

  • Makridakis, S. G., Wheelwright, S. C., and McGee, V. E. (1983), Forecasting: Methods and Applications, 2nd Edition, New York: John Wiley & Sons.

  • McKenzie, E. (1984), “General Exponential Smoothing and the Equivalent ARMA Process,” Journal of Forecasting, 3, 333–344.

  • McKenzie, E. (1986), “Error Analysis for Winters’ Additive Seasonal Forecasting System,” International Journal of Forecasting, 2, 373–382.

  • Montgomery, D. C. and Johnson, L. A. (1976), Forecasting and Time Series Analysis, New York: McGraw-Hill.

  • Morf, M., Sidhu, G. S., and Kailath, T. (1974), “Some New Algorithms for Recursive Estimation on Constant Linear Discrete Time Systems,” IEEE Transactions on Automatic Control, 19, 315–323.

  • Nelson, C. R. (1973), Applied Time Series for Managerial Forecasting, San Francisco: Holden-Day.

  • Newbold, P. (1981), “Some Recent Developments in Time Series Analysis,” International Statistical Review, 49, 53–66.

  • Newton, H. J. and Pagano, M. (1983), “The Finite Memory Prediction of Covariance Stationary Time Series,” SIAM Journal on Scientific and Statistical Computing, 4, 330–339.

  • Pankratz, A. (1983), Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, New York: John Wiley & Sons.

  • Pankratz, A. (1991), Forecasting with Dynamic Regression Models, New York: John Wiley & Sons.

  • Pankratz, A. and Dudley, U. (1987), “Forecast of Power-Transformed Series,” Journal of Forecasting, 6, 239–248.

  • Pearlman, J. G. (1980), “An Algorithm for the Exact Likelihood of a High-Order Autoregressive–Moving Average Process,” Biometrika, 67, 232–233.

  • Priestley, M. B. (1981), Spectral Analysis and Time Series, London: Academic Press.

  • Roberts, S. A. (1982), “A General Class of Holt-Winters Type Forecasting Models,” Management Science, 28, 808–820.

  • Schwarz, G. (1978), “Estimating the Dimension of a Model,” Annals of Statistics, 6, 461–464.

  • Sweet, A. L. (1985), “Computing the Variance of the Forecast Error for the Holt-Winters Seasonal Models,” Journal of Forecasting, 4, 235–243.

  • Winters, P. R. (1960), “Forecasting Sales by Exponentially Weighted Moving Averages,” Management Science, 6, 324–342.

  • Woodfield, T. J. (1987), “Time Series Intervention Analysis Using SAS Software,” in Proceedings of the Twelfth Annual SAS Users Group International Conference, Cary, NC: SAS Institute Inc.

  • Yar, M. and Chatfield, C. (1990), “Prediction Intervals for the Holt-Winters Forecasting Procedure,” International Journal of Forecasting, 6, 127–137.