References

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

  • Aldrin, M. and Damsleth, E. (1989), Forecasting Nonseasonal 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. (1979), An Algorithm for the Exact Likelihood of a Mixed Autoregressive Moving-Average Process, Biometrika, 66, 59.

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

  • 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, Massachusetts: Duxbury Press.

  • Box, G.E.P. and Cox D.R. (1964), An Analysis of Transformations, Journal of Royal Statistical Society B, No. 26, 211–243.

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

  • Box, G.E.P. and Tiao, G.C. (1975), Intervention Analysis with Applications to Economic and Environmental Problems, JASA, 70, 70–79.

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

  • 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(366), 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(386), 355–367.

  • Fair, R.C. (1986), Evaluating the Predictive Accuracy of Models, in Handbook of Econometrics, Vol. 3., Griliches, Z. and Intriligator, M.D., eds., 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, Inc.

  • Greene, W.H. (1993), Econometric Analysis, Second Edition, New York: Macmillan Publishing Company.

  • Hamilton, J. D. (1994), Time Series Analysis, Princeton: 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, Vol 3, No. 1, 57–61.

  • Jones, Richard 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., Wheelwright, S.C., and McGee, V.E. (1983), Forecasting: Methods and Applications, Second Edition, New York: John Wiley & Sons.

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

  • McKenzie, Ed (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, I.E.E.E. Transactions on Automatic Control, AC-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. Joseph and Pagano, Marcello (1983), The Finite Memory Prediction of Covariance Stationary Time Series, SIAM Journal of Scientific and Statistical Computing, 4, 330–339.

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

  • Pankratz, Alan (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, Vol 6, No. 4, 239–248.

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

  • Priestly, M.B. (1981), Spectral Analysis and Time Series, Volume 1: Univariate Series, New York: Academic Press, Inc.

  • 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.

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

  • Woodfield, T.J. (1987), Time Series Intervention Analysis Using SAS Software, Proceedings of the Twelfth Annual SAS Users Group International Conference, 331–339. Cary, NC: SAS Institute Inc.