The efficiency of some forecasting methods applied to annual minimum flow series
Treść / Zawartość
Four methods of forecasting: „no-change", LOESS, local linear regression and Holt-Winters were applied to annual minimum water levels observed at ten cross-sections of two tributaries of the Vistula river. The 1-, 2-, ..., 5-year forecasts were made for each year after some initial year, and four quality measures: bias, root mean square error, mean absolute error and maximum absolute error were calculated for each time series and lead time. The naïve model turned out to be always the worst in it bias and almost always very good, sometimes the best regarding the other measures.
- Cleveland, W. S., Loader, C. (1995) Smoothing by local regression: Principles and methods. Technical Report, AT&T Bell Laboratories, Murray Hill, NY.
- Helsel D. R., Hirsch R. M., Statistical Methods in Water Resources, Elsevier 1997
- Li, X. and Heckman, N. E. (1996) Local linear forecasting. Technical Report 167. Department of Statistics, University of British Columbia, Vancouver.
- NIST 2011, http://www.itl.nist.gov/div898/handbook/pmd/section1/pmd144.htm, (accessed 19.11.2011).