A Quantile Regression Approach to Generating Prediction Intervals

References

• Bookbinder J. H., Lordahl A. Estimation of inventory re-order levels using the bootstrap statistical procedure. IIE Trans. (1989) 21:302–312Crossref, Google Scholar
• Bowerman B. L., Koehler A. B. The appropriateness of Gardner's simple approach and Chebyshev prediction intervals. (1989) . Unpublished paper presented at the 9th International Symposium on Forecasting in Vancouver, B.C., June 18–20Google Scholar
• Business Forecast Systems Forecast Pro for Windows. (1994) . Business Forecast Systems Incorporated, Belmont, MAGoogle Scholar
• Chatfield C. Calculating interval forecasts. J. Bus. Econom. Statist. (1993) 11:121–135Crossref, Google Scholar
• Chatfield C., Yar M. Prediction intervals for multiplicative Holt-Winters. Internat. J. Forecasting (1991) 7:31–37Crossref, Google Scholar
• Gardner E. S. Exponential smoothing: The state of the art. J. Forecasting (1985) 4:1–28Crossref, Google Scholar
• Gardner E. S. A simple method of computing prediction intervals for time-series forecasts. Management Sci. (1988) 34:541–546Link, Google Scholar
• Gardner E. S., McKenzie E. Forecasting trends in time series. Management Sci. (1985) 31:1237–1246Link, Google Scholar
• Gélinas R., Lefrançois P. On the estimation of time-series quantiles using smoothed order statistics. Internat. J. Forecasting (1993) 9:227–243Crossref, Google Scholar
• Gorr W. L., Hsu C. An adaptive filtering procedure for estimating regression quantiles. Management Sci. (1985) 31:1019–1029Link, Google Scholar
• Gould W. W. Quantile regression with bootstrapped standard errors. Stata Tech. Bull. (1992) 9:19–21Google Scholar
• Johnston F. R., Harrison P. J. The variance of lead-time demand. J. Oper. Res. Soc. (1986) 3:303–308Crossref, Google Scholar
• Kinderman A. J., Ramage J. G. Computer generation of normal random numbers. J. Amer. Statist. Assoc. (1976) 71:893–896Crossref, Google Scholar
• Koenker R. W., Bassett G. W. Regression quantiles. Econometrica (1978) 46:33–50Crossref, Google Scholar
• Koenker R. W., Bassett G. W. Robust tests for heteroscedasticity based on regression quantiles. Econometrica (1982) 50:43–62Crossref, Google Scholar
• Ledolter J., Abraham B. Some comments on the initialization of exponential smoothing. J. Forecasting (1984) 3:79–84Crossref, Google Scholar
• Makridakis S., Anderson A., Carbone R., Fildes R., Hibon M., Lewandowski R., Newton J., Parzen E., Winkler R. The accuracy of extrapolation (time series) methods: Results of a forecasting competition. J. Forecasting (1982) 1:111–153Crossref, Google Scholar
• Makridakis S., Winkler R. L. Sampling distributions of post-sample forecast errors. Appl. Statist. (1989) 38:331–342Crossref, Google Scholar
• Meade N., Islam T. Prediction intervals for growth curve forecasts. J. Forecasting (1995) 14:413–430Crossref, Google Scholar
• Roberts S. A. A general class of Holt-Winters type forecasting models. Management Sci. (1982) 28:808–820Link, Google Scholar
• Rogers W. H. Quantile regression standard errors. Stata Tech. Bull. (1992) 9:16–19Google Scholar
• Rosas A. L., Guerrero V. M. Restricted forecasts using exponential smoothing techniques. Internat. J. Forecasting (1994) 10:515–527Crossref, Google Scholar
• Stata (1993) . STATA 3.1, Stata Corporation, College Station, TXGoogle Scholar
• Williams W. H., Goodman M. L. A simple method for the construction of empirical confidence limits for economic forecasts. J. Amer. Statist. Assoc. (1971) 66:752–754Crossref, Google Scholar
• Yar M., Chatfield C. Prediction intervals for the Holt-Winters forecasting procedure. Internat. J. Forecasting (1990) 6:127–137Crossref, Google Scholar