haku: @indexterm Forecasting techniques / yhteensä: 246
viite: 103 / 246
Tekijä:Aldrin, M.
Damsleth, E.
Otsikko:Forecasting non-seasonal time series with missing observations.
Lehti:Journal of Forecasting
1989 : APR-JUN, VOL. 8:2, p. 97-116
Asiasana:FORECASTING TECHNIQUES
TIME SERIES
Kieli:eng
Tiivistelmä:Most forecasting methods are based on equally spaced data. In the case of missing observations the methods have to be modified. Three smoothing methods are considered: 1. simple exponential smoothing; 2. double exponential smoothing; 3. the Holt's method. A new, unified approach is also presented to handle missing data within the smoothing methods. This approach is compared with previously suggested modifications. The comparison is done on 12 real, non-seasonal time series. It is shown that the smoothing methods, properly modified, usually perform well if the time series have a moderate number of missing observations.
SCIMA tietueen numero: 66810
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