论文信息 - Forecasts of power‐transformed series

Forecasts of power‐transformed series

Consider a time series transformed by an instantaneous power function of the Box-Cox type. For a wide range of fractional powers, this paper gives the relative bias in original metric forecasts due to use of the simple inverse retransformation when minimum mean squared error (conditional mean) forecasts are optimal. This bias varies widely according to the characteristics of the data. A fast algorithm is given to find this bias, or to find minimum mean squared error forecasts in the original metric. The results depend on the assumption that the forecast errors in the transformed metric are Gaussian. An example using real data is given.

Alan Pankratz | Underwood Dudley | Underwood Dudley | Alan E. Pankratz

[1] Peter A. Stark. Introduction to Numerical Methods , 1970 .

[2] C. Chatfield,et al. Box‐Jenkins Seasonal Forecasting: Problems in a Case‐Study , 1973 .

[3] C. F. Ansley,et al. A Class of Transformations for Box‐Jenkins Seasonal Models , 1977 .

[4] Clive W. J. Granger,et al. Prediction with a generalized cost of error function , 1969 .

[5] George E. P. Box,et al. Some Comments on a Paper by Chatfield and Prothero and on a Review by Kendall , 1973 .

[6] George E. P. Box,et al. Intervention Analysis with Applications to Economic and Environmental Problems , 1975 .

[7] C. Nelson,et al. Applied Time Series Analysis for Managerial Forecasting. , 1973 .

[8] Paul Newbold,et al. Time series forecasting models involving power transformations , 1984 .

[9] Clive W. J. Granger,et al. Experience with using the Box-Cox transformation when forecasting economic time series , 1979 .

[10] J. Tukey. On the Comparative Anatomy of Transformations , 1957 .

[11] Box Ge,et al. Time series analysis: forecasting and control rev. ed. , 1976 .