Mohammed Yar's research while affiliated with University of Bath and other places
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Publications (2)
Yar and Chatfield (1990) have proposed a method of constructing prediction intervals for the additive Holt-Winters forecasting procedure and this companion paper extends the results to the multiplicative seasonal case. In contrast to the additive case, it is shown that the width of ‘multiplicative’ prediction intervals will depend on the time origi...
Prediction interval formulae are derived for the Holt-Winters forecasting procedure with an additive seasonal effect. The formulae make no assumptions about the ‘true’ underlying model. The results are contrasted with those obtained from various alternative approaches to the calculation of prediction intervals. Some large discrepancies are noted an...
Citations
... We harness the concept of the prediction interval (confidence interval), which provides us an insight of the statistical plausibility of , since determines the triggering of a BLM process. Based on Yar and Chatfield (1990), we define the Prediction Interval (PI) for the HW model: let ( ) = + −̂ ( ) be the forecasting error of the -step-ahead process. We denote with (1) the one-step-ahead forecasting error computed based on the sequence = { 1 , ..., }. ...
... When the data is plotted against time, it could be apparently noted that the data is not constant over time and changes (moreover increases) along with time, especially, the the variation in the seasonal pattern appears to be proportional to the level of the time series. Plotting the series and examining the structure is the most important and essential step in timeseries analysis; preliminary even to adjusting and modeling the data [7]. In this context, the paper has attempted to examine the crop insurance data and to forecast using the basic excel software. ...
